Python Backend Developer Master Program
An intensive 4-month online weekend live engineering cohort (Sat & Sun • 4 hours/day: 2h live faculty lectures + 2h supervised coding labs) covering Python Backend Developer production capstones and 580+ AI interviews, with eligible hiring-drive access under documented placement terms and tuition-refund protection where all policy conditions are met.
- Online Weekend Live Sessions (Sat & Sun • 4 Hours / Day)
- 4 Months (16 Weeks) Comprehensive Finish
- Guaranteed Placement Drives until Placed across 1,050+ top companies
- 26 Production Microservices & Capstones with GitHub code reviews
- 580+ Topic Mock Tests & 1-on-1 AI Voice Technical Interviews
Our Graduates Get Marketed to 1,050+ Global Tech Leaders & Unicorns
Continuous corporate interview referrals until job offer letter issuance:
Online Weekend Master Track: 4 Months of Live Mentorship & Placement Drives
Designed for college students and working professionals, our Online Weekend Master Track delivers intensive 4-hour live sessions every Saturday and Sunday across 16 weeks (4 Months). Complete 128+ hours of live faculty instruction, 26 production capstones, and 580+ AI interviews with unlimited corporate interview drives until you get placed!
Live Architecture & Core Mentorship
2 Hours of interactive enterprise architecture, live faculty coding, and design patterns followed by 2 Hours of supervised capstone development.
Hands-On Labs, Tests & AI Practice
2 Hours of advanced microservices, real-time queues & cloud deployment followed by 2 Hours of timed mock tests and 1-on-1 AI voice interview rounds.
4-Month Master Roadmap to Guaranteed Placement
We transform you into a battle-tested software engineer ready to clear Tier-1 technical and system design interview rounds in 4 months with weekend online sessions.
Architecture & Core Mechanics
Core OOP, memory mechanics, data structures, algorithms & clean design patterns.
Capstones & Microservices
Build production full stack SaaS, microservices, REST APIs, queues & cloud deployment.
System Design & AI Interviews
Simulate live FAANG interview rounds, timed topic mock tests and AI voice evaluations.
Corporate Drives until Placed
Resume marketing, hiring drives across 1,050+ partners, and placement guarantee.
Projected Target CTC After Program
Industry-verified compensation brackets achieved by graduates across 1,050+ hiring partners:
₹8.5L – ₹14L /yr
Software Engineer I, Junior Backend Developer, Full Stack Associate.
- 260+ Hours Live Mentorship
- 26 Capstone Projects on GitHub
- 580+ AI Technical Interview Scorecards
₹14L – ₹24L /yr
Full Stack Java Engineer, Spring Boot Microservices Specialist, Cloud Engineer.
- Kafka Event-Driven Architectures
- Redis Caching & Performance Tuning
- Docker, Kubernetes & AWS CI/CD
₹24L – ₹36L+ /yr
Senior Full Stack Engineer, Microservices Architect, Lead Consultant.
- High-Throughput System Design (LLD/HLD)
- Fault Tolerance & Distributed Transactions
- FAANG System Design Clearing Mentorship
Topic-Wise Curriculum & Practice Hub
124 Modules • 584 Deep-Dive Topics • 584 Integrated Topic Mock Tests & AI Interviews
3 curriculum topics: How Backend Systems Work, Programming Concepts, Backend Responsibilities.
How Backend Systems Work
Understand:; Client; HTTP; Web Server; Application; Database; Response
- Explain the core concepts and architecture of How Backend Systems Work.
- Apply How Backend Systems Work in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Programming Concepts
variables; data types; operators; conditions; loops; functions; algorithms
- Explain the core concepts and architecture of Programming Concepts.
- Apply Programming Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backend Responsibilities
Backend handles:; authentication; authorization; validation; business rules; persistence; integration; security; performance
- Explain the core concepts and architecture of Backend Responsibilities.
- Apply Backend Responsibilities in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Int, Float, Bool, Str, List, Tuple, Set, Dict and 1 more topics.
Int
CORE PYTHON: Int. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Int.
- Apply Int in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Float
CORE PYTHON: Float. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Float.
- Apply Float in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bool
CORE PYTHON: Bool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Bool.
- Apply Bool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Str
CORE PYTHON: Str. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Str.
- Apply Str in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
List
CORE PYTHON: List. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of List.
- Apply List in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tuple
CORE PYTHON: Tuple. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tuple.
- Apply Tuple in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Set
CORE PYTHON: Set. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Set.
- Apply Set in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dict
CORE PYTHON: Dict. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dict.
- Apply Dict in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
None
CORE PYTHON: None. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of None.
- Apply None in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: If, Elif, Else, Match/case, For, While, Break, Continue.
If
CONTROL FLOW: If. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of If.
- Apply If in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Elif
CONTROL FLOW: Elif. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Elif.
- Apply Elif in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Else
CONTROL FLOW: Else. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Else.
- Apply Else in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Match/case
CONTROL FLOW: Match/case. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Match/case.
- Apply Match/case in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
For
CONTROL FLOW: For. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of For.
- Apply For in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
While
CONTROL FLOW: While. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of While.
- Apply While in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Break
CONTROL FLOW: Break. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Break.
- Apply Break in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Continue
CONTROL FLOW: Continue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Continue.
- Apply Continue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Parameters, Return values, Keyword arguments, Default values, *args, Kwargs, Lambda, Scope.
Parameters
FUNCTIONS: Parameters. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Parameters.
- Apply Parameters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Return values
FUNCTIONS: Return values. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Return values.
- Apply Return values in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keyword arguments
FUNCTIONS: Keyword arguments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Keyword arguments.
- Apply Keyword arguments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Default values
FUNCTIONS: Default values. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Default values.
- Apply Default values in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
*args
FUNCTIONS: *args. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of *args.
- Apply *args in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kwargs
FUNCTIONS: Kwargs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Kwargs.
- Apply Kwargs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lambda
FUNCTIONS: Lambda. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lambda.
- Apply Lambda in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scope
FUNCTIONS: Scope. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scope.
- Apply Scope in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: List, Tuple, Set, Dictionary, Performance characteristics, Mutability, Hashing, Common use cases.
List
PYTHON COLLECTIONS: List. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of List.
- Apply List in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tuple
PYTHON COLLECTIONS: Tuple. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tuple.
- Apply Tuple in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Set
PYTHON COLLECTIONS: Set. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Set.
- Apply Set in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dictionary
PYTHON COLLECTIONS: Dictionary. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dictionary.
- Apply Dictionary in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Performance characteristics
PYTHON COLLECTIONS: Performance characteristics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Performance characteristics.
- Apply Performance characteristics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mutability
PYTHON COLLECTIONS: Mutability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mutability.
- Apply Mutability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Hashing
PYTHON COLLECTIONS: Hashing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Hashing.
- Apply Hashing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Common use cases
PYTHON COLLECTIONS: Common use cases. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Common use cases.
- Apply Common use cases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Classes, Objects, Constructors, Encapsulation, Inheritance, Polymorphism, Abstraction, Composition.
Classes
OOP: Classes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Classes.
- Apply Classes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Objects
OOP: Objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Objects.
- Apply Objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Constructors
OOP: Constructors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Constructors.
- Apply Constructors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Encapsulation
OOP: Encapsulation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Encapsulation.
- Apply Encapsulation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Inheritance
OOP: Inheritance. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Inheritance.
- Apply Inheritance in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Polymorphism
OOP: Polymorphism. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Polymorphism.
- Apply Polymorphism in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Abstraction
OOP: Abstraction. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Abstraction.
- Apply Abstraction in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Composition
OOP: Composition. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Composition.
- Apply Composition in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: S — Single Responsibility, O — Open/Closed, L — Liskov Substitution, I — Interface Segregation, D — Dependency Inversion.
S — Single Responsibility
SOLID: S — Single Responsibility. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of S — Single Responsibility.
- Apply S — Single Responsibility in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
O — Open/Closed
SOLID: O — Open/Closed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of O — Open/Closed.
- Apply O — Open/Closed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
L — Liskov Substitution
SOLID: L — Liskov Substitution. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of L — Liskov Substitution.
- Apply L — Liskov Substitution in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
I — Interface Segregation
SOLID: I — Interface Segregation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of I — Interface Segregation.
- Apply I — Interface Segregation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
D — Dependency Inversion
SOLID: D — Dependency Inversion. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of D — Dependency Inversion.
- Apply D — Dependency Inversion in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Decorators, Generators, Iterators, Context managers, Closures, Comprehensions, Descriptors concepts, Magic methods and 1 more topics.
Decorators
ADVANCED PYTHON: Decorators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Decorators.
- Apply Decorators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generators
ADVANCED PYTHON: Generators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Generators.
- Apply Generators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Iterators
ADVANCED PYTHON: Iterators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Iterators.
- Apply Iterators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context managers
ADVANCED PYTHON: Context managers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Context managers.
- Apply Context managers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Closures
ADVANCED PYTHON: Closures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Closures.
- Apply Closures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Comprehensions
ADVANCED PYTHON: Comprehensions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Comprehensions.
- Apply Comprehensions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Descriptors concepts
ADVANCED PYTHON: Descriptors concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Descriptors concepts.
- Apply Descriptors concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Magic methods
ADVANCED PYTHON: Magic methods. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Magic methods.
- Apply Magic methods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dataclasses
ADVANCED PYTHON: Dataclasses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dataclasses.
- Apply Dataclasses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Type hints, Optional, Union, Literal, TypedDict concepts, Protocol concepts, Generics, TypeVar and 1 more topics.
Type hints
PYTHON TYPING: Type hints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Type hints.
- Apply Type hints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optional
PYTHON TYPING: Optional. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Optional.
- Apply Optional in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Union
PYTHON TYPING: Union. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Union.
- Apply Union in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Literal
PYTHON TYPING: Literal. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Literal.
- Apply Literal in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TypedDict concepts
PYTHON TYPING: TypedDict concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of TypedDict concepts.
- Apply TypedDict concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Protocol concepts
PYTHON TYPING: Protocol concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Protocol concepts.
- Apply Protocol concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generics
PYTHON TYPING: Generics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Generics.
- Apply Generics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TypeVar
PYTHON TYPING: TypeVar. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of TypeVar.
- Apply TypeVar in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Callable typing
PYTHON TYPING: Callable typing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Callable typing.
- Apply Callable typing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Custom exceptions, Exception hierarchy, Exception translation, Retryable vs non-retryable errors.
Custom exceptions
EXCEPTIONS: Custom exceptions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Custom exceptions.
- Apply Custom exceptions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exception hierarchy
EXCEPTIONS: Exception hierarchy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exception hierarchy.
- Apply Exception hierarchy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exception translation
EXCEPTIONS: Exception translation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exception translation.
- Apply Exception translation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retryable vs non-retryable errors
EXCEPTIONS: Retryable vs non-retryable errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retryable vs non-retryable errors.
- Apply Retryable vs non-retryable errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Files, Pathlib, JSON, CSV, Serialization concepts.
Files
FILES & SERIALIZATION: Files. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Files.
- Apply Files in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pathlib
FILES & SERIALIZATION: Pathlib. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pathlib.
- Apply Pathlib in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSON
FILES & SERIALIZATION: JSON. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JSON.
- Apply JSON in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSV
FILES & SERIALIZATION: CSV. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CSV.
- Apply CSV in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Serialization concepts
FILES & SERIALIZATION: Serialization concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Serialization concepts.
- Apply Serialization concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Structured logging, Contextual logs, Exception logging, Correlation IDs, Passwords, JWT tokens, API keys, Secrets and 1 more topics.
Structured logging
LOGGING: Structured logging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Structured logging.
- Apply Structured logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Contextual logs
LOGGING: Contextual logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Contextual logs.
- Apply Contextual logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exception logging
LOGGING: Exception logging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exception logging.
- Apply Exception logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Correlation IDs
LOGGING: Correlation IDs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Correlation IDs.
- Apply Correlation IDs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Passwords
LOGGING: Passwords. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Passwords.
- Apply Passwords in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JWT tokens
LOGGING: JWT tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JWT tokens.
- Apply JWT tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API keys
LOGGING: API keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API keys.
- Apply API keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secrets
LOGGING: Secrets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secrets.
- Apply Secrets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unnecessary personal data
LOGGING: Unnecessary personal data. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unnecessary personal data.
- Apply Unnecessary personal data in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Object references, Mutability, Garbage collection, Reference counting concepts, Cycles, Memory leaks.
Object references
PYTHON MEMORY MODEL: Object references. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Object references.
- Apply Object references in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mutability
PYTHON MEMORY MODEL: Mutability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mutability.
- Apply Mutability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Garbage collection
PYTHON MEMORY MODEL: Garbage collection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Garbage collection.
- Apply Garbage collection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reference counting concepts
PYTHON MEMORY MODEL: Reference counting concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reference counting concepts.
- Apply Reference counting concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cycles
PYTHON MEMORY MODEL: Cycles. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cycles.
- Apply Cycles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memory leaks
PYTHON MEMORY MODEL: Memory leaks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Memory leaks.
- Apply Memory leaks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Large datasets, Streaming, Memory-efficient processing.
Large datasets
ITERATORS & GENERATORS: Large datasets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Large datasets.
- Apply Large datasets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
ITERATORS & GENERATORS: Streaming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streaming.
- Apply Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memory-efficient processing
ITERATORS & GENERATORS: Memory-efficient processing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Memory-efficient processing.
- Apply Memory-efficient processing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Concurrency, Parallelism, Asynchronous I/O.
Concurrency
CONCURRENCY FUNDAMENTALS: Concurrency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Concurrency.
- Apply Concurrency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Parallelism
CONCURRENCY FUNDAMENTALS: Parallelism. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Parallelism.
- Apply Parallelism in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Asynchronous I/O
CONCURRENCY FUNDAMENTALS: Asynchronous I/O. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Asynchronous I/O.
- Apply Asynchronous I/O in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Thread, Locks, Race conditions, Thread safety, GIL concepts.
Thread
THREADING: Thread. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Thread.
- Apply Thread in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locks
THREADING: Locks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Locks.
- Apply Locks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Race conditions
THREADING: Race conditions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Race conditions.
- Apply Race conditions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Thread safety
THREADING: Thread safety. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Thread safety.
- Apply Thread safety in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GIL concepts
THREADING: GIL concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of GIL concepts.
- Apply GIL concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Process, Process pool, IPC concepts.
Process
MULTIPROCESSING: Process. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Process.
- Apply Process in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Process pool
MULTIPROCESSING: Process pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Process pool.
- Apply Process pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
IPC concepts
MULTIPROCESSING: IPC concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of IPC concepts.
- Apply IPC concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Event loop, Coroutine, Task, Await, Gather, Timeout, Cancellation, Semaphore.
Event loop
ASYNCIO: Event loop. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Event loop.
- Apply Event loop in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Coroutine
ASYNCIO: Coroutine. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Coroutine.
- Apply Coroutine in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Task
ASYNCIO: Task. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Task.
- Apply Task in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Await
ASYNCIO: Await. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Await.
- Apply Await in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Gather
ASYNCIO: Gather. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Gather.
- Apply Gather in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timeout
ASYNCIO: Timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Timeout.
- Apply Timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cancellation
ASYNCIO: Cancellation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cancellation.
- Apply Cancellation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Semaphore
ASYNCIO: Semaphore. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Semaphore.
- Apply Semaphore in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Structured Concurrency Concepts.
Structured Concurrency Concepts
Teach modern async architecture and safe cancellation patterns.
- Explain the core concepts and architecture of Structured Concurrency Concepts.
- Apply Structured Concurrency Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: What free-threaded Python means, Compatibility concerns, Concurrency implications, Why normal Python builds and async architectures still remain highly relevant, 75 MCQs, 50 Coding Tasks.
What free-threaded Python means
FREE-THREADED PYTHON AWARENESS: What free-threaded Python means. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of What free-threaded Python means.
- Apply What free-threaded Python means in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Compatibility concerns
FREE-THREADED PYTHON AWARENESS: Compatibility concerns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Compatibility concerns.
- Apply Compatibility concerns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Concurrency implications
FREE-THREADED PYTHON AWARENESS: Concurrency implications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Concurrency implications.
- Apply Concurrency implications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Why normal Python builds and async architectures still remain highly relevant
FREE-THREADED PYTHON AWARENESS: Why normal Python builds and async architectures still remain highly relevant. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Why normal Python builds and async architectures still remain highly relevant.
- Apply Why normal Python builds and async architectures still remain highly relevant in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
75 MCQs
FREE-THREADED PYTHON AWARENESS: 75 MCQs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of 75 MCQs.
- Apply 75 MCQs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
50 Coding Tasks
FREE-THREADED PYTHON AWARENESS: 50 Coding Tasks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of 50 Coding Tasks.
- Apply 50 Coding Tasks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
15 curriculum topics: Arrays/lists, Strings, Hash maps, Sets, Stacks, Queues, Heaps, Trees and 7 more topics.
Arrays/lists
DATA STRUCTURES & ALGORITHMS: Arrays/lists. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Arrays/lists.
- Apply Arrays/lists in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strings
DATA STRUCTURES & ALGORITHMS: Strings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Strings.
- Apply Strings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Hash maps
DATA STRUCTURES & ALGORITHMS: Hash maps. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Hash maps.
- Apply Hash maps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sets
DATA STRUCTURES & ALGORITHMS: Sets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sets.
- Apply Sets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stacks
DATA STRUCTURES & ALGORITHMS: Stacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Stacks.
- Apply Stacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queues
DATA STRUCTURES & ALGORITHMS: Queues. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queues.
- Apply Queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Heaps
DATA STRUCTURES & ALGORITHMS: Heaps. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Heaps.
- Apply Heaps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Trees
DATA STRUCTURES & ALGORITHMS: Trees. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Trees.
- Apply Trees in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Graphs fundamentals
DATA STRUCTURES & ALGORITHMS: Graphs fundamentals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Graphs fundamentals.
- Apply Graphs fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sorting
DATA STRUCTURES & ALGORITHMS: Sorting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sorting.
- Apply Sorting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Searching
DATA STRUCTURES & ALGORITHMS: Searching. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Searching.
- Apply Searching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Recursion
DATA STRUCTURES & ALGORITHMS: Recursion. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Recursion.
- Apply Recursion in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Binary search
DATA STRUCTURES & ALGORITHMS: Binary search. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Binary search.
- Apply Binary search in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sliding window
DATA STRUCTURES & ALGORITHMS: Sliding window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sliding window.
- Apply Sliding window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Two pointers
DATA STRUCTURES & ALGORITHMS: Two pointers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Two pointers.
- Apply Two pointers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Relational model, Tables, Rows, Columns, Schema, Keys, Constraints.
Relational model
DATABASE FUNDAMENTALS: Relational model. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Relational model.
- Apply Relational model in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tables
DATABASE FUNDAMENTALS: Tables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tables.
- Apply Tables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rows
DATABASE FUNDAMENTALS: Rows. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rows.
- Apply Rows in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Columns
DATABASE FUNDAMENTALS: Columns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Columns.
- Apply Columns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schema
DATABASE FUNDAMENTALS: Schema. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schema.
- Apply Schema in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keys
DATABASE FUNDAMENTALS: Keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Keys.
- Apply Keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Constraints
DATABASE FUNDAMENTALS: Constraints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Constraints.
- Apply Constraints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: SELECT, INSERT, UPDATE, DELETE, Joins, GROUP BY, HAVING, Subqueries.
SELECT
SQL: SELECT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SELECT.
- Apply SELECT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
INSERT
SQL: INSERT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of INSERT.
- Apply INSERT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UPDATE
SQL: UPDATE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UPDATE.
- Apply UPDATE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DELETE
SQL: DELETE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DELETE.
- Apply DELETE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Joins
SQL: Joins. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Joins.
- Apply Joins in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GROUP BY
SQL: GROUP BY. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of GROUP BY.
- Apply GROUP BY in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HAVING
SQL: HAVING. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of HAVING.
- Apply HAVING in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Subqueries
SQL: Subqueries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Subqueries.
- Apply Subqueries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: CTE, Window functions, CASE, Transactions, Indexes, Execution plans, Query optimization.
CTE
ADVANCED SQL: CTE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CTE.
- Apply CTE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Window functions
ADVANCED SQL: Window functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Window functions.
- Apply Window functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CASE
ADVANCED SQL: CASE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CASE.
- Apply CASE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
ADVANCED SQL: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
ADVANCED SQL: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Execution plans
ADVANCED SQL: Execution plans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Execution plans.
- Apply Execution plans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query optimization
ADVANCED SQL: Query optimization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query optimization.
- Apply Query optimization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Schema design, Data types, Indexes, Constraints, Transactions, Locking, Isolation, JSONB and 1 more topics.
Schema design
POSTGRESQL: Schema design. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schema design.
- Apply Schema design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Data types
POSTGRESQL: Data types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Data types.
- Apply Data types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
POSTGRESQL: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Constraints
POSTGRESQL: Constraints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Constraints.
- Apply Constraints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
POSTGRESQL: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locking
POSTGRESQL: Locking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Locking.
- Apply Locking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Isolation
POSTGRESQL: Isolation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Isolation.
- Apply Isolation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSONB
POSTGRESQL: JSONB. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JSONB.
- Apply JSONB in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection management
POSTGRESQL: Connection management. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection management.
- Apply Connection management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Atomicity, Consistency, Isolation, Durability.
Atomicity
TRANSACTIONS: Atomicity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Atomicity.
- Apply Atomicity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consistency
TRANSACTIONS: Consistency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Consistency.
- Apply Consistency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Isolation
TRANSACTIONS: Isolation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Isolation.
- Apply Isolation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Durability
TRANSACTIONS: Durability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Durability.
- Apply Durability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Read Committed, Repeatable Read, Serializable concepts, Dirty reads, Non-repeatable reads, Phantom reads, Lost updates.
Read Committed
ISOLATION LEVELS: Read Committed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Read Committed.
- Apply Read Committed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repeatable Read
ISOLATION LEVELS: Repeatable Read. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Repeatable Read.
- Apply Repeatable Read in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Serializable concepts
ISOLATION LEVELS: Serializable concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Serializable concepts.
- Apply Serializable concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dirty reads
ISOLATION LEVELS: Dirty reads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dirty reads.
- Apply Dirty reads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Non-repeatable reads
ISOLATION LEVELS: Non-repeatable reads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Non-repeatable reads.
- Apply Non-repeatable reads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Phantom reads
ISOLATION LEVELS: Phantom reads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Phantom reads.
- Apply Phantom reads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lost updates
ISOLATION LEVELS: Lost updates. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lost updates.
- Apply Lost updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: B-tree concepts, Composite indexes, Selectivity, Index order, Write overhead.
B-tree concepts
INDEXING: B-tree concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of B-tree concepts.
- Apply B-tree concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Composite indexes
INDEXING: Composite indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Composite indexes.
- Apply Composite indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Selectivity
INDEXING: Selectivity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Selectivity.
- Apply Selectivity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Index order
INDEXING: Index order. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Index order.
- Apply Index order in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Write overhead
INDEXING: Write overhead. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Write overhead.
- Apply Write overhead in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: EXPLAIN, EXPLAIN ANALYZE, Sequential scans, Index scans, Join choices.
EXPLAIN
QUERY OPTIMIZATION: EXPLAIN. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of EXPLAIN.
- Apply EXPLAIN in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
EXPLAIN ANALYZE
QUERY OPTIMIZATION: EXPLAIN ANALYZE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of EXPLAIN ANALYZE.
- Apply EXPLAIN ANALYZE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sequential scans
QUERY OPTIMIZATION: Sequential scans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sequential scans.
- Apply Sequential scans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Index scans
QUERY OPTIMIZATION: Index scans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Index scans.
- Apply Index scans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Join choices
QUERY OPTIMIZATION: Join choices. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Join choices.
- Apply Join choices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Request, Response, Method, Headers, Body, Cookies, Status codes, HTTPS/TLS concepts.
Request
HTTP FUNDAMENTALS: Request. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Request.
- Apply Request in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Response
HTTP FUNDAMENTALS: Response. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Response.
- Apply Response in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Method
HTTP FUNDAMENTALS: Method. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Method.
- Apply Method in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Headers
HTTP FUNDAMENTALS: Headers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Headers.
- Apply Headers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Body
HTTP FUNDAMENTALS: Body. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Body.
- Apply Body in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cookies
HTTP FUNDAMENTALS: Cookies. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cookies.
- Apply Cookies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status codes
HTTP FUNDAMENTALS: Status codes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Status codes.
- Apply Status codes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTPS/TLS concepts
HTTP FUNDAMENTALS: HTTPS/TLS concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of HTTPS/TLS concepts.
- Apply HTTPS/TLS concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Resources, URL design, HTTP semantics, Statelessness.
Resources
REST API DESIGN: Resources. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Resources.
- Apply Resources in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
URL design
REST API DESIGN: URL design. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of URL design.
- Apply URL design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTP semantics
REST API DESIGN: HTTP semantics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of HTTP semantics.
- Apply HTTP semantics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Statelessness
REST API DESIGN: Statelessness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Statelessness.
- Apply Statelessness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Input, Validation, Output, Errors, Authorization, Idempotency, Rate limits.
Input
API CONTRACT DESIGN: Input. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Input.
- Apply Input in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
API CONTRACT DESIGN: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Output
API CONTRACT DESIGN: Output. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Output.
- Apply Output in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
API CONTRACT DESIGN: Errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Errors.
- Apply Errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorization
API CONTRACT DESIGN: Authorization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authorization.
- Apply Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
API CONTRACT DESIGN: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limits
API CONTRACT DESIGN: Rate limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limits.
- Apply Rate limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Application, Routers, Path operations, Path parameters, Query parameters, Request bodies.
Application
FASTAPI FUNDAMENTALS: Application. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Application.
- Apply Application in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routers
FASTAPI FUNDAMENTALS: Routers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routers.
- Apply Routers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Path operations
FASTAPI FUNDAMENTALS: Path operations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Path operations.
- Apply Path operations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Path parameters
FASTAPI FUNDAMENTALS: Path parameters. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Path parameters.
- Apply Path parameters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query parameters
FASTAPI FUNDAMENTALS: Query parameters. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query parameters.
- Apply Query parameters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Request bodies
FASTAPI FUNDAMENTALS: Request bodies. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Request bodies.
- Apply Request bodies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: BaseModel, Nested objects, Validators, Custom validation, Serialization, Settings concepts.
BaseModel
PYDANTIC: BaseModel. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of BaseModel.
- Apply BaseModel in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Nested objects
PYDANTIC: Nested objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Nested objects.
- Apply Nested objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validators
PYDANTIC: Validators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validators.
- Apply Validators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Custom validation
PYDANTIC: Custom validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Custom validation.
- Apply Custom validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Serialization
PYDANTIC: Serialization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Serialization.
- Apply Serialization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Settings concepts
PYDANTIC: Settings concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Settings concepts.
- Apply Settings concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Database sessions, Authentication, Authorization, Tenant resolution, Shared validation.
Database sessions
FASTAPI DEPENDENCY INJECTION: Database sessions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database sessions.
- Apply Database sessions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
FASTAPI DEPENDENCY INJECTION: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authorization
FASTAPI DEPENDENCY INJECTION: Authorization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authorization.
- Apply Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tenant resolution
FASTAPI DEPENDENCY INJECTION: Tenant resolution. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tenant resolution.
- Apply Tenant resolution in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Shared validation
FASTAPI DEPENDENCY INJECTION: Shared validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Shared validation.
- Apply Shared validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Response Models.
Response Models
Use typed API contracts.
- Explain the core concepts and architecture of Response Models.
- Apply Response Models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Error Handling.
Error Handling
Standard error:; json; {; "code": "ORDER_NOT_FOUND",; "message": "Order was not found",; "trace_id": "..."; }
- Explain the core concepts and architecture of Error Handling.
- Apply Error Handling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Fastapi Async.
Fastapi Async
Teach when to use:; async def; versus:; def; FastAPI's official guidance distinguishes asynchronous I/O libraries from blocking libraries and allows both styles to coexist appropriately. ([FastAPI][4])
- Explain the core concepts and architecture of Fastapi Async.
- Apply Fastapi Async in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Engines, Sessions, Declarative models, Queries, Relationships, Transactions, Async SQLAlchemy concepts.
Engines
SQLALCHEMY: Engines. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Engines.
- Apply Engines in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sessions
SQLALCHEMY: Sessions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sessions.
- Apply Sessions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Declarative models
SQLALCHEMY: Declarative models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Declarative models.
- Apply Declarative models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queries
SQLALCHEMY: Queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queries.
- Apply Queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relationships
SQLALCHEMY: Relationships. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Relationships.
- Apply Relationships in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
SQLALCHEMY: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async SQLAlchemy concepts
SQLALCHEMY: Async SQLAlchemy concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async SQLAlchemy concepts.
- Apply Async SQLAlchemy concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Migrations, Revision, Upgrade, Downgrade, Schema versioning.
Migrations
ALEMBIC: Migrations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Migrations.
- Apply Migrations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Revision
ALEMBIC: Revision. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Revision.
- Apply Revision in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Upgrade
ALEMBIC: Upgrade. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Upgrade.
- Apply Upgrade in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Downgrade
ALEMBIC: Downgrade. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Downgrade.
- Apply Downgrade in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schema versioning
ALEMBIC: Schema versioning. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schema versioning.
- Apply Schema versioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Pool size, Max overflow, Timeout, Connection leaks.
Pool size
CONNECTION POOLING: Pool size. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pool size.
- Apply Pool size in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Max overflow
CONNECTION POOLING: Max overflow. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Max overflow.
- Apply Max overflow in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timeout
CONNECTION POOLING: Timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Timeout.
- Apply Timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection leaks
CONNECTION POOLING: Connection leaks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection leaks.
- Apply Connection leaks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: FastAPI, PostgreSQL, SQLAlchemy, Alembic, Validation, Pagination, Filtering, Search and 2 more topics.
FastAPI
FASTAPI PROJECT STRUCTURE: FastAPI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of FastAPI.
- Apply FastAPI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL
FASTAPI PROJECT STRUCTURE: PostgreSQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PostgreSQL.
- Apply PostgreSQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SQLAlchemy
FASTAPI PROJECT STRUCTURE: SQLAlchemy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SQLAlchemy.
- Apply SQLAlchemy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Alembic
FASTAPI PROJECT STRUCTURE: Alembic. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Alembic.
- Apply Alembic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
FASTAPI PROJECT STRUCTURE: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
FASTAPI PROJECT STRUCTURE: Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pagination.
- Apply Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Filtering
FASTAPI PROJECT STRUCTURE: Filtering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filtering.
- Apply Filtering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Search
FASTAPI PROJECT STRUCTURE: Search. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Search.
- Apply Search in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OpenAPI
FASTAPI PROJECT STRUCTURE: OpenAPI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of OpenAPI.
- Apply OpenAPI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tests
FASTAPI PROJECT STRUCTURE: Tests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tests.
- Apply Tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Django.
Django
Teach modern Django architecture.; Django 6.1 is the current feature release as of August 2026. ([Django Project][3])
- Explain the core concepts and architecture of Django.
- Apply Django in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Models, QuerySets, Relationships, Indexes, Transactions, Select_related, Prefetch_related.
Models
DJANGO ORM: Models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Models.
- Apply Models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
QuerySets
DJANGO ORM: QuerySets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of QuerySets.
- Apply QuerySets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relationships
DJANGO ORM: Relationships. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Relationships.
- Apply Relationships in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
DJANGO ORM: Indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Indexes.
- Apply Indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transactions
DJANGO ORM: Transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transactions.
- Apply Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Select_related
DJANGO ORM: Select_related. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Select_related.
- Apply Select_related in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prefetch_related
DJANGO ORM: Prefetch_related. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prefetch_related.
- Apply Prefetch_related in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Serializers, Views, Viewsets, Routers, Authentication, Permissions, Pagination, Filtering.
Serializers
DJANGO REST: Serializers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Serializers.
- Apply Serializers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Views
DJANGO REST: Views. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Views.
- Apply Views in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Viewsets
DJANGO REST: Viewsets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Viewsets.
- Apply Viewsets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routers
DJANGO REST: Routers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routers.
- Apply Routers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
DJANGO REST: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Permissions
DJANGO REST: Permissions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Permissions.
- Apply Permissions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
DJANGO REST: Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pagination.
- Apply Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Filtering
DJANGO REST: Filtering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filtering.
- Apply Filtering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Django Admin.
Django Admin
Use for internal administrative tools.
- Explain the core concepts and architecture of Django Admin.
- Apply Django Admin in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: APIs, Async, Microservices, AI backends, Complete business platforms, Admin, Mature ORM, Integrated authentication.
APIs
FASTAPI VS DJANGO: APIs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of APIs.
- Apply APIs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async
FASTAPI VS DJANGO: Async. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async.
- Apply Async in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Microservices
FASTAPI VS DJANGO: Microservices. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Microservices.
- Apply Microservices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI backends
FASTAPI VS DJANGO: AI backends. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI backends.
- Apply AI backends in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Complete business platforms
FASTAPI VS DJANGO: Complete business platforms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Complete business platforms.
- Apply Complete business platforms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Admin
FASTAPI VS DJANGO: Admin. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Admin.
- Apply Admin in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mature ORM
FASTAPI VS DJANGO: Mature ORM. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mature ORM.
- Apply Mature ORM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Integrated authentication
FASTAPI VS DJANGO: Integrated authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Integrated authentication.
- Apply Integrated authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Session, Basic concepts, Token, JWT, OAuth2.
Session
AUTHENTICATION: Session. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Session.
- Apply Session in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Basic concepts
AUTHENTICATION: Basic concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Basic concepts.
- Apply Basic concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token
AUTHENTICATION: Token. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token.
- Apply Token in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JWT
AUTHENTICATION: JWT. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JWT.
- Apply JWT in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
OAuth2
AUTHENTICATION: OAuth2. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of OAuth2.
- Apply OAuth2 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Access tokens, Refresh tokens, Claims, Signatures, Expiry, Rotation, Revocation concepts.
Access tokens
JWT: Access tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Access tokens.
- Apply Access tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Refresh tokens
JWT: Refresh tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Refresh tokens.
- Apply Refresh tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Claims
JWT: Claims. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Claims.
- Apply Claims in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Signatures
JWT: Signatures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Signatures.
- Apply Signatures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expiry
JWT: Expiry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Expiry.
- Apply Expiry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rotation
JWT: Rotation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rotation.
- Apply Rotation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Revocation concepts
JWT: Revocation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Revocation concepts.
- Apply Revocation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rbac.
Rbac
Example:; CUSTOMER; SUPPORT; MANAGER; ADMIN
- Explain the core concepts and architecture of Rbac.
- Apply Rbac in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Object-Level Authorization.
Object-Level Authorization
Scenario:; User ID 100 requests:; GET /users/200/orders; Authentication is valid.; Authorization must reject access.
- Explain the core concepts and architecture of Object-Level Authorization.
- Apply Object-Level Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Authorization Code, PKCE, Client Credentials, Scopes, Resource server concepts.
Authorization Code
OAUTH2: Authorization Code. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authorization Code.
- Apply Authorization Code in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PKCE
OAUTH2: PKCE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PKCE.
- Apply PKCE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Client Credentials
OAUTH2: Client Credentials. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Client Credentials.
- Apply Client Credentials in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scopes
OAUTH2: Scopes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scopes.
- Apply Scopes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Resource server concepts
OAUTH2: Resource server concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Resource server concepts.
- Apply Resource server concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Oidc.
Oidc
Understand identity layer on OAuth2.
- Explain the core concepts and architecture of Oidc.
- Apply Oidc in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: SQL injection, Broken authorization, CORS, CSRF, XSS awareness, Rate limiting, Password hashing, Secure cookies and 1 more topics.
SQL injection
API SECURITY: SQL injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SQL injection.
- Apply SQL injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Broken authorization
API SECURITY: Broken authorization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Broken authorization.
- Apply Broken authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CORS
API SECURITY: CORS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CORS.
- Apply CORS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSRF
API SECURITY: CSRF. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CSRF.
- Apply CSRF in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
XSS awareness
API SECURITY: XSS awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of XSS awareness.
- Apply XSS awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limiting
API SECURITY: Rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limiting.
- Apply Rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Password hashing
API SECURITY: Password hashing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Password hashing.
- Apply Password hashing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secure cookies
API SECURITY: Secure cookies. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secure cookies.
- Apply Secure cookies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secret management
API SECURITY: Secret management. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secret management.
- Apply Secret management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Organization, Users, Roles, Tenant isolation, JWT/OAuth concepts, Audit.
Organization
MULTI-TENANT SECURITY: Organization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Organization.
- Apply Organization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Users
MULTI-TENANT SECURITY: Users. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Users.
- Apply Users in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Roles
MULTI-TENANT SECURITY: Roles. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Roles.
- Apply Roles in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tenant isolation
MULTI-TENANT SECURITY: Tenant isolation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tenant isolation.
- Apply Tenant isolation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JWT/OAuth concepts
MULTI-TENANT SECURITY: JWT/OAuth concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JWT/OAuth concepts.
- Apply JWT/OAuth concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Audit
MULTI-TENANT SECURITY: Audit. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Audit.
- Apply Audit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Strings, Hashes concepts, Caching, TTL, Cache-aside, Invalidation, Distributed locks concepts, Rate limiting.
Strings
REDIS: Strings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Strings.
- Apply Strings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Hashes concepts
REDIS: Hashes concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Hashes concepts.
- Apply Hashes concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Caching
REDIS: Caching. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Caching.
- Apply Caching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TTL
REDIS: TTL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of TTL.
- Apply TTL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache-aside
REDIS: Cache-aside. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache-aside.
- Apply Cache-aside in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Invalidation
REDIS: Invalidation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Invalidation.
- Apply Invalidation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Distributed locks concepts
REDIS: Distributed locks concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Distributed locks concepts.
- Apply Distributed locks concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limiting
REDIS: Rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limiting.
- Apply Rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Cache Hit, Cache Miss, Cache Stampede, Stale Data, Invalidation.
Cache Hit
CACHE ENGINEERING: Cache Hit. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache Hit.
- Apply Cache Hit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache Miss
CACHE ENGINEERING: Cache Miss. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache Miss.
- Apply Cache Miss in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache Stampede
CACHE ENGINEERING: Cache Stampede. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache Stampede.
- Apply Cache Stampede in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stale Data
CACHE ENGINEERING: Stale Data. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Stale Data.
- Apply Stale Data in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Invalidation
CACHE ENGINEERING: Invalidation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Invalidation.
- Apply Invalidation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Email, Reports, Exports, Image processing, AI jobs.
BACKGROUND JOBS: Email. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Email.
- Apply Email in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reports
BACKGROUND JOBS: Reports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reports.
- Apply Reports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exports
BACKGROUND JOBS: Exports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exports.
- Apply Exports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Image processing
BACKGROUND JOBS: Image processing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Image processing.
- Apply Image processing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI jobs
BACKGROUND JOBS: AI jobs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI jobs.
- Apply AI jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Task, Worker, Broker, Result backend, Retry, Scheduling.
Task
CELERY: Task. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Task.
- Apply Task in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Worker
CELERY: Worker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Worker.
- Apply Worker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Broker
CELERY: Broker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Broker.
- Apply Broker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Result backend
CELERY: Result backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Result backend.
- Apply Result backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
CELERY: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scheduling
CELERY: Scheduling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scheduling.
- Apply Scheduling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Queue Design.
Queue Design
Job lifecycle:; QUEUED; RUNNING; COMPLETED; or; FAILED
- Explain the core concepts and architecture of Queue Design.
- Apply Queue Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Queue, Visibility timeout, Retry, Dead-letter queue.
Queue
AWS SQS: Queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queue.
- Apply Queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Visibility timeout
AWS SQS: Visibility timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Visibility timeout.
- Apply Visibility timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
AWS SQS: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dead-letter queue
AWS SQS: Dead-letter queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dead-letter queue.
- Apply Dead-letter queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Sns.
Sns
Teach publish-subscribe concepts.
- Explain the core concepts and architecture of Sns.
- Apply Sns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Command, Event.
Command
EVENT-DRIVEN ARCHITECTURE: Command. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Command.
- Apply Command in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event
EVENT-DRIVEN ARCHITECTURE: Event. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Event.
- Apply Event in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Broker, Topic, Partition, Producer, Consumer, Consumer group, Offset, Ordering and 1 more topics.
Broker
KAFKA FUNDAMENTALS: Broker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Broker.
- Apply Broker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Topic
KAFKA FUNDAMENTALS: Topic. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Topic.
- Apply Topic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Partition
KAFKA FUNDAMENTALS: Partition. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Partition.
- Apply Partition in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Producer
KAFKA FUNDAMENTALS: Producer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Producer.
- Apply Producer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer
KAFKA FUNDAMENTALS: Consumer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Consumer.
- Apply Consumer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Consumer group
KAFKA FUNDAMENTALS: Consumer group. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Consumer group.
- Apply Consumer group in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Offset
KAFKA FUNDAMENTALS: Offset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Offset.
- Apply Offset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Ordering
KAFKA FUNDAMENTALS: Ordering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Ordering.
- Apply Ordering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Delivery semantics
KAFKA FUNDAMENTALS: Delivery semantics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Delivery semantics.
- Apply Delivery semantics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Idempotency.
Idempotency
Critical backend engineering topic.; Example:; Client retries:; POST /payments; Backend must not create two charges.; IDEMPOTENCY LAB; Request:; http; Idempotency-Key: abc123; Second identical request returns same business result.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Service boundaries, Loose coupling, Independent deployment, Database ownership.
Service boundaries
MICROSERVICES: Service boundaries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Service boundaries.
- Apply Service boundaries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loose coupling
MICROSERVICES: Loose coupling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Loose coupling.
- Apply Loose coupling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Independent deployment
MICROSERVICES: Independent deployment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Independent deployment.
- Apply Independent deployment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database ownership
MICROSERVICES: Database ownership. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database ownership.
- Apply Database ownership in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Modular Monolith First.
Modular Monolith First
Students should understand why not every system requires microservices.
- Explain the core concepts and architecture of Modular Monolith First.
- Apply Modular Monolith First in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: REST, Events, Queues, Asynchronous workflows.
REST
SERVICE COMMUNICATION: REST. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of REST.
- Apply REST in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
SERVICE COMMUNICATION: Events. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Events.
- Apply Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queues
SERVICE COMMUNICATION: Queues. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queues.
- Apply Queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Asynchronous workflows
SERVICE COMMUNICATION: Asynchronous workflows. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Asynchronous workflows.
- Apply Asynchronous workflows in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Timeouts.
Timeouts
Every external call needs deliberate timeout behavior.
- Explain the core concepts and architecture of Timeouts.
- Apply Timeouts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Retryable errors, Exponential backoff, Jitter, Max attempts.
Retryable errors
RETRIES: Retryable errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retryable errors.
- Apply Retryable errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exponential backoff
RETRIES: Exponential backoff. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exponential backoff.
- Apply Exponential backoff in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Jitter
RETRIES: Jitter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Jitter.
- Apply Jitter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Max attempts
RETRIES: Max attempts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Max attempts.
- Apply Max attempts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Circuit Breaker.
Circuit Breaker
Introduce resilience pattern.
- Explain the core concepts and architecture of Circuit Breaker.
- Apply Circuit Breaker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Local transactions, Distributed consistency, Saga concepts, Compensating operations.
Local transactions
DISTRIBUTED TRANSACTIONS: Local transactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Local transactions.
- Apply Local transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Distributed consistency
DISTRIBUTED TRANSACTIONS: Distributed consistency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Distributed consistency.
- Apply Distributed consistency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Saga concepts
DISTRIBUTED TRANSACTIONS: Saga concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Saga concepts.
- Apply Saga concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Compensating operations
DISTRIBUTED TRANSACTIONS: Compensating operations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Compensating operations.
- Apply Compensating operations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: FastAPI, PostgreSQL, Redis, Kafka concepts, Background worker, Idempotency, Outbox.
FastAPI
TRANSACTIONAL OUTBOX: FastAPI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of FastAPI.
- Apply FastAPI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL
TRANSACTIONAL OUTBOX: PostgreSQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PostgreSQL.
- Apply PostgreSQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis
TRANSACTIONAL OUTBOX: Redis. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redis.
- Apply Redis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kafka concepts
TRANSACTIONAL OUTBOX: Kafka concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Kafka concepts.
- Apply Kafka concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Background worker
TRANSACTIONAL OUTBOX: Background worker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Background worker.
- Apply Background worker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
TRANSACTIONAL OUTBOX: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Outbox
TRANSACTIONAL OUTBOX: Outbox. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Outbox.
- Apply Outbox in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Signatures, Delivery, Retries, Duplicate delivery, Idempotency.
Signatures
WEBHOOKS: Signatures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Signatures.
- Apply Signatures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Delivery
WEBHOOKS: Delivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Delivery.
- Apply Delivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retries
WEBHOOKS: Retries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retries.
- Apply Retries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duplicate delivery
WEBHOOKS: Duplicate delivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Duplicate delivery.
- Apply Duplicate delivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
WEBHOOKS: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Upload, Download, Validation, MIME type, File limits.
Upload
FILE APIs: Upload. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Upload.
- Apply Upload in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Download
FILE APIs: Download. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Download.
- Apply Download in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
FILE APIs: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
MIME type
FILE APIs: MIME type. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of MIME type.
- Apply MIME type in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File limits
FILE APIs: File limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File limits.
- Apply File limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Documents, Images, Reports, Exports.
Documents
S3: Documents. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Documents.
- Apply Documents in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Images
S3: Images. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Images.
- Apply Images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reports
S3: Reports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reports.
- Apply Reports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exports
S3: Exports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exports.
- Apply Exports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Presigned Urls.
Presigned Urls
Avoid routing large uploads unnecessarily through application server.
- Explain the core concepts and architecture of Presigned Urls.
- Apply Presigned Urls in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Chat, Real-time updates, Notifications.
Chat
WEBSOCKETS: Chat. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Chat.
- Apply Chat in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Real-time updates
WEBSOCKETS: Real-time updates. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Real-time updates.
- Apply Real-time updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
WEBSOCKETS: Notifications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Notifications.
- Apply Notifications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Progress, Streaming, AI output.
Progress
SERVER-SENT EVENTS: Progress. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Progress.
- Apply Progress in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
SERVER-SENT EVENTS: Streaming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streaming.
- Apply Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI output
SERVER-SENT EVENTS: AI output. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI output.
- Apply AI output in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: SQL search, PostgreSQL full-text concepts, Elasticsearch/OpenSearch awareness.
SQL search
SEARCH: SQL search. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SQL search.
- Apply SQL search in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL full-text concepts
SEARCH: PostgreSQL full-text concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PostgreSQL full-text concepts.
- Apply PostgreSQL full-text concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Elasticsearch/OpenSearch awareness
SEARCH: Elasticsearch/OpenSearch awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Elasticsearch/OpenSearch awareness.
- Apply Elasticsearch/OpenSearch awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Offset, Cursor/Keyset.
Offset
API PAGINATION: Offset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Offset.
- Apply Offset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cursor/Keyset
API PAGINATION: Cursor/Keyset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cursor/Keyset.
- Apply Cursor/Keyset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Fixed window, Sliding window, Token bucket concepts.
Fixed window
API RATE LIMITING: Fixed window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fixed window.
- Apply Fixed window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sliding window
API RATE LIMITING: Sliding window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sliding window.
- Apply Sliding window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token bucket concepts
API RATE LIMITING: Token bucket concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token bucket concepts.
- Apply Token bucket concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Tests, Fixtures, Parametrization, Exceptions, Markers.
Tests
PYTEST: Tests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tests.
- Apply Tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fixtures
PYTEST: Fixtures. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fixtures.
- Apply Fixtures in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Parametrization
PYTEST: Parametrization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Parametrization.
- Apply Parametrization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exceptions
PYTEST: Exceptions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exceptions.
- Apply Exceptions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Markers
PYTEST: Markers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Markers.
- Apply Markers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: External APIs, Email providers, Payment clients.
External APIs
MOCKING: External APIs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of External APIs.
- Apply External APIs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Email providers
MOCKING: Email providers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Email providers.
- Apply Email providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Payment clients
MOCKING: Payment clients. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Payment clients.
- Apply Payment clients in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Validation, Status codes, Auth, Permissions, Database, Errors.
Validation
FASTAPI TESTING: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status codes
FASTAPI TESTING: Status codes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Status codes.
- Apply Status codes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Auth
FASTAPI TESTING: Auth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Auth.
- Apply Auth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Permissions
FASTAPI TESTING: Permissions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Permissions.
- Apply Permissions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database
FASTAPI TESTING: Database. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database.
- Apply Database in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
FASTAPI TESTING: Errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Errors.
- Apply Errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Database Integration Testing.
Database Integration Testing
Use isolated test DB.
- Explain the core concepts and architecture of Database Integration Testing.
- Apply Database Integration Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: PostgreSQL, Redis, Kafka where relevant.
PostgreSQL
TESTCONTAINERS CONCEPTS: PostgreSQL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PostgreSQL.
- Apply PostgreSQL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis
TESTCONTAINERS CONCEPTS: Redis. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redis.
- Apply Redis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Kafka where relevant
TESTCONTAINERS CONCEPTS: Kafka where relevant. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Kafka where relevant.
- Apply Kafka where relevant in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Contract Testing.
Contract Testing
Understand API compatibility.
- Explain the core concepts and architecture of Contract Testing.
- Apply Contract Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Load, Stress, Spike, Soak, K6, Locust concepts.
Load
LOAD TESTING: Load. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Load.
- Apply Load in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stress
LOAD TESTING: Stress. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Stress.
- Apply Stress in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spike
LOAD TESTING: Spike. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Spike.
- Apply Spike in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Soak
LOAD TESTING: Soak. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Soak.
- Apply Soak in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
K6
LOAD TESTING: K6. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of K6.
- Apply K6 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locust concepts
LOAD TESTING: Locust concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Locust concepts.
- Apply Locust concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Throughput, P50, P95, P99, Error rate.
Throughput
PERFORMANCE METRICS: Throughput. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Throughput.
- Apply Throughput in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P50
PERFORMANCE METRICS: P50. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P50.
- Apply P50 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P95
PERFORMANCE METRICS: P95. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P95.
- Apply P95 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P99
PERFORMANCE METRICS: P99. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P99.
- Apply P99 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error rate
PERFORMANCE METRICS: Error rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error rate.
- Apply Error rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Query time, Connection pool, N+1, Index, Locking.
Query time
DATABASE PERFORMANCE: Query time. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query time.
- Apply Query time in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection pool
DATABASE PERFORMANCE: Connection pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection pool.
- Apply Connection pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
N+1
DATABASE PERFORMANCE: N+1. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of N+1.
- Apply N+1 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Index
DATABASE PERFORMANCE: Index. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Index.
- Apply Index in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locking
DATABASE PERFORMANCE: Locking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Locking.
- Apply Locking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Async Performance.
Async Performance
Common issue:; Async endpoint calls blocking code.; Result:; Event loop is blocked.; Students learn to recognize and fix it.
- Explain the core concepts and architecture of Async Performance.
- Apply Async Performance in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Large objects, Unbounded caches, Generators, Streaming responses.
Large objects
MEMORY PERFORMANCE: Large objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Large objects.
- Apply Large objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unbounded caches
MEMORY PERFORMANCE: Unbounded caches. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unbounded caches.
- Apply Unbounded caches in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generators
MEMORY PERFORMANCE: Generators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Generators.
- Apply Generators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming responses
MEMORY PERFORMANCE: Streaming responses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streaming responses.
- Apply Streaming responses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Logs, Metrics, Traces.
Logs
OBSERVABILITY: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Metrics
OBSERVABILITY: Metrics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Metrics.
- Apply Metrics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Traces
OBSERVABILITY: Traces. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Traces.
- Apply Traces in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Structured Logging.
Structured Logging
Example:; json; {; "request_id": "...",; "route": "/orders",; "user_id": 100,; "duration_ms": 88; }
- Explain the core concepts and architecture of Structured Logging.
- Apply Structured Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Requests, Errors, Latency, DB pool, Cache hit ratio, Queue depth.
Requests
METRICS: Requests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Requests.
- Apply Requests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
METRICS: Errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Errors.
- Apply Errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Latency
METRICS: Latency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Latency.
- Apply Latency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB pool
METRICS: DB pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DB pool.
- Apply DB pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache hit ratio
METRICS: Cache hit ratio. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache hit ratio.
- Apply Cache hit ratio in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue depth
METRICS: Queue depth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queue depth.
- Apply Queue depth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Trace, Span, Context.
Trace
OPENTELEMETRY: Trace. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Trace.
- Apply Trace in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Span
OPENTELEMETRY: Span. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Span.
- Apply Span in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context
OPENTELEMETRY: Context. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Context.
- Apply Context in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Alerting.
Alerting
Example:; P95 > 2 sec; or; error_rate > 5%
- Explain the core concepts and architecture of Alerting.
- Apply Alerting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Images, Containers, Dockerfile, Multi-stage build, Networking, Volumes, Environment variables.
Images
DOCKER: Images. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Images.
- Apply Images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Containers
DOCKER: Containers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Containers.
- Apply Containers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dockerfile
DOCKER: Dockerfile. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dockerfile.
- Apply Dockerfile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-stage build
DOCKER: Multi-stage build. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Multi-stage build.
- Apply Multi-stage build in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Networking
DOCKER: Networking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Networking.
- Apply Networking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Volumes
DOCKER: Volumes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Volumes.
- Apply Volumes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment variables
DOCKER: Environment variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Environment variables.
- Apply Environment variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Docker Compose.
Docker Compose
Local environment:; text; FastAPI; PostgreSQL; Redis; Worker; Kafka/Queue
- Explain the core concepts and architecture of Docker Compose.
- Apply Docker Compose in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Filesystem, Permissions, Processes, Environment variables, Logs, Networking basics.
Filesystem
LINUX: Filesystem. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filesystem.
- Apply Filesystem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Permissions
LINUX: Permissions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Permissions.
- Apply Permissions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Processes
LINUX: Processes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Processes.
- Apply Processes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment variables
LINUX: Environment variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Environment variables.
- Apply Environment variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logs
LINUX: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Networking basics
LINUX: Networking basics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Networking basics.
- Apply Networking basics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Pods, Deployments, Services, ConfigMaps, Secrets, Health probes, Scaling, Rolling deployment.
Pods
KUBERNETES: Pods. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pods.
- Apply Pods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Deployments
KUBERNETES: Deployments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Deployments.
- Apply Deployments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Services
KUBERNETES: Services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Services.
- Apply Services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ConfigMaps
KUBERNETES: ConfigMaps. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ConfigMaps.
- Apply ConfigMaps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secrets
KUBERNETES: Secrets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secrets.
- Apply Secrets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Health probes
KUBERNETES: Health probes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Health probes.
- Apply Health probes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scaling
KUBERNETES: Scaling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scaling.
- Apply Scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rolling deployment
KUBERNETES: Rolling deployment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rolling deployment.
- Apply Rolling deployment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Iam.
Aws Iam
Teach least privilege.
- Explain the core concepts and architecture of Aws Iam.
- Apply Aws Iam in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Ec2.
Ec2
Deploy Python backend.
- Explain the core concepts and architecture of Ec2.
- Apply Ec2 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rds.
Rds
Host PostgreSQL.
- Explain the core concepts and architecture of Rds.
- Apply Rds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: S3.
S3
Object storage.
- Explain the core concepts and architecture of S3.
- Apply S3 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Lambda.
Aws Lambda
Teach event-driven serverless backend concepts.
- Explain the core concepts and architecture of Aws Lambda.
- Apply Aws Lambda in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Sqs/Sns.
Aws Sqs/Sns
Queue-based architecture.
- Explain the core concepts and architecture of Aws Sqs/Sns.
- Apply Aws Sqs/Sns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Step Functions Awareness.
Step Functions Awareness
Teach workflow orchestration concepts for serverless services.
- Explain the core concepts and architecture of Step Functions Awareness.
- Apply Step Functions Awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Logs, Metrics, Alerts.
Logs
CLOUDWATCH: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Metrics
CLOUDWATCH: Metrics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Metrics.
- Apply Metrics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Alerts
CLOUDWATCH: Alerts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Alerts.
- Apply Alerts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Ci/Cd.
Ci/Cd
Pipeline:; Commit; Lint; Unit Tests; Integration Tests; Security Scan; Docker Build; Deploy
- Explain the core concepts and architecture of Ci/Cd.
- Apply Ci/Cd in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Github Actions.
Github Actions
Hands-on pipeline.
- Explain the core concepts and architecture of Github Actions.
- Apply Github Actions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Environments.
Environments
Use:; DEV; TEST; STAGING; PRODUCTION
- Explain the core concepts and architecture of Environments.
- Apply Environments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Secret Management.
Secret Management
Never commit .env production credentials.
- Explain the core concepts and architecture of Secret Management.
- Apply Secret Management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Rolling, Blue/green, Canary concepts.
Rolling
DEPLOYMENT STRATEGIES: Rolling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rolling.
- Apply Rolling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Blue/green
DEPLOYMENT STRATEGIES: Blue/green. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blue/green.
- Apply Blue/green in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Canary concepts
DEPLOYMENT STRATEGIES: Canary concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Canary concepts.
- Apply Canary concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Repository, Service, Factory, Strategy, Adapter, Observer, Dependency Injection, Unit of Work concepts.
Repository
DESIGN PATTERNS: Repository. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Repository.
- Apply Repository in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service
DESIGN PATTERNS: Service. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Service.
- Apply Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Factory
DESIGN PATTERNS: Factory. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Factory.
- Apply Factory in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strategy
DESIGN PATTERNS: Strategy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Strategy.
- Apply Strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Adapter
DESIGN PATTERNS: Adapter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Adapter.
- Apply Adapter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Observer
DESIGN PATTERNS: Observer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Observer.
- Apply Observer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Injection
DESIGN PATTERNS: Dependency Injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency Injection.
- Apply Dependency Injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unit of Work concepts
DESIGN PATTERNS: Unit of Work concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unit of Work concepts.
- Apply Unit of Work concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Domain, Application, Infrastructure, Delivery/API.
Domain
CLEAN ARCHITECTURE: Domain. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Domain.
- Apply Domain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Application
CLEAN ARCHITECTURE: Application. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Application.
- Apply Application in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Infrastructure
CLEAN ARCHITECTURE: Infrastructure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Infrastructure.
- Apply Infrastructure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Delivery/API
CLEAN ARCHITECTURE: Delivery/API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Delivery/API.
- Apply Delivery/API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Low-Level Design.
Low-Level Design
Problems:; 1. Parking Lot; 2. Library; 3. Notification System; 4. Payment Service; 5. Task Scheduler; 6. Rate Limiter; 7. Order Service; 8. URL Shortener
- Explain the core concepts and architecture of Low-Level Design.
- Apply Low-Level Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
21 curriculum topics: Requirements, Traffic, API, Database, Cache, Queue, Storage, Scaling and 13 more topics.
Requirements
SYSTEM DESIGN: Requirements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Requirements.
- Apply Requirements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Traffic
SYSTEM DESIGN: Traffic. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Traffic.
- Apply Traffic in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API
SYSTEM DESIGN: API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API.
- Apply API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database
SYSTEM DESIGN: Database. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database.
- Apply Database in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache
SYSTEM DESIGN: Cache. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache.
- Apply Cache in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue
SYSTEM DESIGN: Queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queue.
- Apply Queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Storage
SYSTEM DESIGN: Storage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Storage.
- Apply Storage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scaling
SYSTEM DESIGN: Scaling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scaling.
- Apply Scaling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reliability
SYSTEM DESIGN: Reliability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reliability.
- Apply Reliability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Security
SYSTEM DESIGN: Security. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Security.
- Apply Security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Observability
SYSTEM DESIGN: Observability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Observability.
- Apply Observability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
URL Shortener
SYSTEM DESIGN: URL Shortener. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of URL Shortener.
- Apply URL Shortener in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Payment Backend
SYSTEM DESIGN: Payment Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Payment Backend.
- Apply Payment Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Booking Platform
SYSTEM DESIGN: Booking Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Booking Platform.
- Apply Booking Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notification Service
SYSTEM DESIGN: Notification Service. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Notification Service.
- Apply Notification Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Chat Backend
SYSTEM DESIGN: Chat Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Chat Backend.
- Apply Chat Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File Processing Platform
SYSTEM DESIGN: File Processing Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File Processing Platform.
- Apply File Processing Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SaaS Backend
SYSTEM DESIGN: SaaS Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SaaS Backend.
- Apply SaaS Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Learning Management Backend
SYSTEM DESIGN: Learning Management Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Learning Management Backend.
- Apply Learning Management Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
E-Commerce Backend
SYSTEM DESIGN: E-Commerce Backend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of E-Commerce Backend.
- Apply E-Commerce Backend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI Processing Platform
SYSTEM DESIGN: AI Processing Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI Processing Platform.
- Apply AI Processing Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
27 curriculum topics: Database, Blocking async, External dependency, Connection pool, DB pool, Locks, Event loop blocking, Downstream dependency and 19 more topics.
Database
PRODUCTION DEBUGGING: Database. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database.
- Apply Database in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Blocking async
PRODUCTION DEBUGGING: Blocking async. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blocking async.
- Apply Blocking async in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
External dependency
PRODUCTION DEBUGGING: External dependency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of External dependency.
- Apply External dependency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Connection pool
PRODUCTION DEBUGGING: Connection pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection pool.
- Apply Connection pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB pool
PRODUCTION DEBUGGING: DB pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DB pool.
- Apply DB pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Locks
PRODUCTION DEBUGGING: Locks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Locks.
- Apply Locks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event loop blocking
PRODUCTION DEBUGGING: Event loop blocking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Event loop blocking.
- Apply Event loop blocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Downstream dependency
PRODUCTION DEBUGGING: Downstream dependency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Downstream dependency.
- Apply Downstream dependency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache
PRODUCTION DEBUGGING: Cache. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache.
- Apply Cache in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Object retention
PRODUCTION DEBUGGING: Object retention. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Object retention.
- Apply Object retention in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Background workers
PRODUCTION DEBUGGING: Background workers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Background workers.
- Apply Background workers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Large in-memory objects
PRODUCTION DEBUGGING: Large in-memory objects. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Large in-memory objects.
- Apply Large in-memory objects in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retries
PRODUCTION DEBUGGING: Retries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retries.
- Apply Retries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
PRODUCTION DEBUGGING: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Webhooks
PRODUCTION DEBUGGING: Webhooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Webhooks.
- Apply Webhooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue redelivery
PRODUCTION DEBUGGING: Queue redelivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queue redelivery.
- Apply Queue redelivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Acknowledgement
PRODUCTION DEBUGGING: Acknowledgement. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Acknowledgement.
- Apply Acknowledgement in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Visibility timeout
PRODUCTION DEBUGGING: Visibility timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Visibility timeout.
- Apply Visibility timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Requests/sec
PRODUCTION DEBUGGING: Requests/sec. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Requests/sec.
- Apply Requests/sec in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P95
PRODUCTION DEBUGGING: P95. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P95.
- Apply P95 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error Rate
PRODUCTION DEBUGGING: Error Rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error Rate.
- Apply Error Rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU
PRODUCTION DEBUGGING: CPU. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CPU.
- Apply CPU in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL Connections
PRODUCTION DEBUGGING: PostgreSQL Connections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PostgreSQL Connections.
- Apply PostgreSQL Connections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis
PRODUCTION DEBUGGING: Redis. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redis.
- Apply Redis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Traces
PRODUCTION DEBUGGING: Traces. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Traces.
- Apply Traces in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logs
PRODUCTION DEBUGGING: Logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logs.
- Apply Logs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Slow queries
PRODUCTION DEBUGGING: Slow queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Slow queries.
- Apply Slow queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: LLM APIs, Streaming, Structured output, Tool calls concepts, Embeddings, Vector search concepts, RAG fundamentals.
LLM APIs
AI BACKEND INTEGRATION: LLM APIs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of LLM APIs.
- Apply LLM APIs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
AI BACKEND INTEGRATION: Streaming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streaming.
- Apply Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Structured output
AI BACKEND INTEGRATION: Structured output. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Structured output.
- Apply Structured output in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tool calls concepts
AI BACKEND INTEGRATION: Tool calls concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tool calls concepts.
- Apply Tool calls concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embeddings
AI BACKEND INTEGRATION: Embeddings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Embeddings.
- Apply Embeddings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Vector search concepts
AI BACKEND INTEGRATION: Vector search concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Vector search concepts.
- Apply Vector search concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RAG fundamentals
AI BACKEND INTEGRATION: RAG fundamentals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of RAG fundamentals.
- Apply RAG fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Ai Backend Architecture.
Ai Backend Architecture
Architecture:; Client; FastAPI; AI Service; LLM / Vector Store / Tools
- Explain the core concepts and architecture of Ai Backend Architecture.
- Apply Ai Backend Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Ai Job Processing.
Ai Job Processing
Long AI request:; POST /research; returns:; 202 Accepted; with:; job_id; Then:; GET /jobs/{id}
- Explain the core concepts and architecture of Ai Job Processing.
- Apply Ai Job Processing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
12 curriculum topics: Quotas, Token tracking, Rate limits, Prompt injection awareness, Tenant security, Output validation, FastAPI, Authentication and 4 more topics.
Quotas
AI COST & SECURITY: Quotas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Quotas.
- Apply Quotas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token tracking
AI COST & SECURITY: Token tracking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token tracking.
- Apply Token tracking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limits
AI COST & SECURITY: Rate limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limits.
- Apply Rate limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prompt injection awareness
AI COST & SECURITY: Prompt injection awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prompt injection awareness.
- Apply Prompt injection awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tenant security
AI COST & SECURITY: Tenant security. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tenant security.
- Apply Tenant security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Output validation
AI COST & SECURITY: Output validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Output validation.
- Apply Output validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
FastAPI
AI COST & SECURITY: FastAPI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of FastAPI.
- Apply FastAPI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication
AI COST & SECURITY: Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication.
- Apply Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
AI COST & SECURITY: Streaming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streaming.
- Apply Streaming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Document retrieval
AI COST & SECURITY: Document retrieval. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Document retrieval.
- Apply Document retrieval in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limit
AI COST & SECURITY: Rate limit. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limit.
- Apply Rate limit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Usage tracking
AI COST & SECURITY: Usage tracking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Usage tracking.
- Apply Usage tracking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
26 Hands-On Production Capstones & Microservices
Build, deploy, and showcase real-world enterprise architectures on GitHub to prove your production engineering readiness:
Enterprise E-Commerce Microservices & Event-Driven Streaming Platform
Architected with Spring Boot 3.3, Apache Kafka event streams, Redis distributed caching, React 19 UI, and PostgreSQL. Features distributed ACID transaction sagas, payment webhook handling, dynamic inventory locking, and Dockerized Kubernetes deployment.
High-Throughput Banking & Core Transaction Engine
Concurrent multithreaded financial transaction ledger with ACID compliance, optimistic row locking, idempotent payment endpoints, and audit logging.
Real-Time Logistics & Fleet Tracking Service
Bi-directional live vehicle telemetry dashboard processing 10,000+ geo-coordinate events/sec with live map rendering and ETA calculations.
Multi-Tenant SaaS Subscription & Webhook Gateway
Multi-tenant automated billing engine with webhook signature verification, dynamic token bucket rate-limiting, and tenant data isolation schemas.
Distributed URL Shortener & Analytics System (Bitly Scale)
Low-latency URL redirection engine with distributed ID generation (Snowflake), sub-5ms Redis caching, and real-time click analytics.
Automated Cloud DevOps CI/CD Pipeline on AWS
Production containerization pipeline with automated testing, sonar code quality gates, container image vulnerability scanning, and zero-downtime rolling deploys.
AI-Powered Code Reviewer & Assessment Engine
Automated coding interview evaluator that parses Java AST trees, detects algorithmic time complexity, and simulates 1-on-1 voice technical interview feedback.
MockAttempt Academy vs. Traditional Bootcamps & Self-Study
Transparent side-by-side comparison of daily schedule, duration, curriculum, and placement support:
| Feature & Deliverables | MockAttempt Fast-Track Track | Expensive Bootcamps | Self-Study / YouTube |
|---|---|---|---|
| Live Weekend Schedule | Sat & Sun (4 Hours / Day) | 1 - 1.5 Hours / Day | Self-Paced / Inconsistent |
| Duration to Placement Readiness | 4 Months (16 Weeks Weekend) | 6 - 9 Months | 12+ Months (Uncertain) |
| Candidate Placement Guarantee | Unlimited Drives until Placed (or Full Refund) | Limited to 3-6 Months only | None (Apply blindly) |
| Topic Mock Tests & AI Interviews | Integrated for Every Topic (580+ Rounds) | End of Course Only | None |
| Tuition Fee | ₹49,999 ₹98,999 | ₹1,20,000 - ₹2,50,000 | Free (No Mentorship/Jobs) |
Institutional Course Assurances & 100% Placement Policy
100% Job Placement Guarantee
Our placement team arranges unlimited corporate interview drives across 1,050+ hiring partners until you receive an official offer letter. If unplaced, 100% of your tuition fee is refunded.
1-on-1 Expert Faculty Mentorship
Every cohort is taught live by seasoned lead architects from Tier-1 product companies with daily live coding and supervised code reviews.
Frequently Asked Questions
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