Python Full Stack 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 Full Stack 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
96 Modules • 543 Deep-Dive Topics • 543 Integrated Topic Mock Tests & AI Interviews
4 curriculum topics: How the Web Works, Client/Server Architecture, HTTP, Status Codes.
How the Web Works
Learn:; Browser; server; DNS; domain; IP; HTTP; HTTPS; frontend; backend; database; Architecture:; Browser → API → Application → Database
- Explain the core concepts and architecture of How the Web Works.
- Apply How the Web Works in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Client/Server Architecture
Understand request lifecycle.
- Explain the core concepts and architecture of Client/Server Architecture.
- Apply Client/Server Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
HTTP
Learn:; GET; POST; PUT; PATCH; DELETE
- Explain the core concepts and architecture of HTTP.
- Apply HTTP in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status Codes
Examples:; 200; 201; 400; 401; 403; 404; 409; 422; 500
- 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.
10 curriculum topics: Semantic HTML, Headings, Forms, Inputs, Buttons, Tables, Links, Images and 2 more topics.
Semantic HTML
HTML5: Semantic HTML. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Semantic HTML.
- Apply Semantic HTML in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Headings
HTML5: Headings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Headings.
- Apply Headings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Forms
HTML5: Forms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Forms.
- Apply Forms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Inputs
HTML5: Inputs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Inputs.
- Apply Inputs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Buttons
HTML5: Buttons. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Buttons.
- Apply Buttons in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tables
HTML5: 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.
Links
HTML5: Links. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Links.
- Apply Links in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Images
HTML5: 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.
Accessibility fundamentals
HTML5: Accessibility fundamentals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Accessibility fundamentals.
- Apply Accessibility fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SEO-friendly markup
HTML5: SEO-friendly markup. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SEO-friendly markup.
- Apply SEO-friendly markup in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Selectors, Box model, Positioning, Flexbox, CSS Grid, Responsive design, Media queries, Animations and 1 more topics.
Selectors
CSS3: Selectors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Selectors.
- Apply Selectors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Box model
CSS3: Box model. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Box model.
- Apply Box model in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Positioning
CSS3: Positioning. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Positioning.
- Apply Positioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Flexbox
CSS3: Flexbox. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Flexbox.
- Apply Flexbox in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSS Grid
CSS3: CSS Grid. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CSS Grid.
- Apply CSS Grid in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Responsive design
CSS3: Responsive design. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Responsive design.
- Apply Responsive design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Media queries
CSS3: Media queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Media queries.
- Apply Media queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Animations
CSS3: Animations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Animations.
- Apply Animations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transitions
CSS3: Transitions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transitions.
- Apply Transitions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Desktop, Tablet, Android, IPhone.
Desktop
RESPONSIVE DEVELOPMENT: Desktop. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Desktop.
- Apply Desktop in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tablet
RESPONSIVE DEVELOPMENT: Tablet. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tablet.
- Apply Tablet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Android
RESPONSIVE DEVELOPMENT: Android. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Android.
- Apply Android in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
IPhone
RESPONSIVE DEVELOPMENT: IPhone. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of IPhone.
- Apply IPhone in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Variables, Let/const, Types, Functions, Arrays, Objects, Operators, Loops and 1 more topics.
Variables
JAVASCRIPT FUNDAMENTALS: Variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Variables.
- Apply Variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Let/const
JAVASCRIPT FUNDAMENTALS: Let/const. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Let/const.
- Apply Let/const in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Types
JAVASCRIPT FUNDAMENTALS: Types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Types.
- Apply Types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Functions
JAVASCRIPT FUNDAMENTALS: Functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Functions.
- Apply Functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Arrays
JAVASCRIPT FUNDAMENTALS: Arrays. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Arrays.
- Apply Arrays in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Objects
JAVASCRIPT FUNDAMENTALS: 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.
Operators
JAVASCRIPT FUNDAMENTALS: Operators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Operators.
- Apply Operators in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loops
JAVASCRIPT FUNDAMENTALS: Loops. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Loops.
- Apply Loops in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conditions
JAVASCRIPT FUNDAMENTALS: Conditions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Conditions.
- Apply Conditions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Arrow functions, Destructuring, Spread/rest, Modules, Template literals, Optional chaining, Nullish coalescing.
Arrow functions
MODERN JAVASCRIPT: Arrow functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Arrow functions.
- Apply Arrow functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Destructuring
MODERN JAVASCRIPT: Destructuring. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Destructuring.
- Apply Destructuring in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Spread/rest
MODERN JAVASCRIPT: Spread/rest. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Spread/rest.
- Apply Spread/rest in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules
MODERN JAVASCRIPT: Modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Modules.
- Apply Modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Template literals
MODERN JAVASCRIPT: Template literals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Template literals.
- Apply Template literals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optional chaining
MODERN JAVASCRIPT: Optional chaining. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Optional chaining.
- Apply Optional chaining in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Nullish coalescing
MODERN JAVASCRIPT: Nullish coalescing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Nullish coalescing.
- Apply Nullish coalescing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Callbacks, Promises, Async, Await, Fetch API, Error handling.
Callbacks
ASYNCHRONOUS JAVASCRIPT: Callbacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Callbacks.
- Apply Callbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promises
ASYNCHRONOUS JAVASCRIPT: Promises. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Promises.
- Apply Promises in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async
ASYNCHRONOUS JAVASCRIPT: 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.
Await
ASYNCHRONOUS JAVASCRIPT: 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.
Fetch API
ASYNCHRONOUS JAVASCRIPT: Fetch API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fetch API.
- Apply Fetch API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error handling
ASYNCHRONOUS JAVASCRIPT: Error handling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
8 curriculum topics: Variables, Numbers, Strings, Booleans, Lists, Tuples, Sets, Dictionaries.
Variables
PYTHON FUNDAMENTALS: Variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Variables.
- Apply Variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Numbers
PYTHON FUNDAMENTALS: Numbers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Numbers.
- Apply Numbers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strings
PYTHON FUNDAMENTALS: 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.
Booleans
PYTHON FUNDAMENTALS: Booleans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Booleans.
- Apply Booleans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lists
PYTHON FUNDAMENTALS: Lists. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lists.
- Apply Lists in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tuples
PYTHON FUNDAMENTALS: Tuples. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tuples.
- Apply Tuples in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sets
PYTHON FUNDAMENTALS: 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.
Dictionaries
PYTHON FUNDAMENTALS: Dictionaries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dictionaries.
- Apply Dictionaries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: If, Elif, Else, For, While, Break, Continue, Comprehensions.
If
PYTHON 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
PYTHON 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
PYTHON 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.
For
PYTHON 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
PYTHON 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
PYTHON 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
PYTHON 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.
Comprehensions
PYTHON CONTROL FLOW: 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.
8 curriculum topics: Parameters, Keyword arguments, Defaults, *args, Kwargs, Return, Scope, Lambda.
Parameters
PYTHON 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.
Keyword arguments
PYTHON 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.
Defaults
PYTHON FUNCTIONS: Defaults. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Defaults.
- Apply Defaults in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
*args
PYTHON 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
PYTHON 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.
Return
PYTHON FUNCTIONS: Return. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Return.
- Apply Return in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scope
PYTHON 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.
Lambda
PYTHON 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.
8 curriculum topics: Classes, Objects, Constructors, Inheritance, Polymorphism, Encapsulation, Abstraction, Composition.
Classes
PYTHON 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
PYTHON 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
PYTHON 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.
Inheritance
PYTHON 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
PYTHON 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.
Encapsulation
PYTHON 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.
Abstraction
PYTHON 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
PYTHON 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.
8 curriculum topics: Decorators, Generators, Iterators, Context managers, Closures, Descriptors concepts, Magic methods, Dataclasses.
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.
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.
7 curriculum topics: Type hints, Optional, Union, Generics, Protocol concepts, Typed collections, Static analysis concepts.
Type hints
PYTHON TYPE SYSTEM: 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 TYPE SYSTEM: 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 TYPE SYSTEM: 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.
Generics
PYTHON TYPE SYSTEM: 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.
Protocol concepts
PYTHON TYPE SYSTEM: 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.
Typed collections
PYTHON TYPE SYSTEM: Typed collections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Typed collections.
- Apply Typed collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Static analysis concepts
PYTHON TYPE SYSTEM: Static analysis concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Static analysis concepts.
- Apply Static analysis concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Try, Except, Else, Finally, Raise, Custom exceptions.
Try
EXCEPTION HANDLING: Try. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Try.
- Apply Try in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Except
EXCEPTION HANDLING: Except. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Except.
- Apply Except in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Else
EXCEPTION HANDLING: 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.
Finally
EXCEPTION HANDLING: Finally. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Finally.
- Apply Finally in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Raise
EXCEPTION HANDLING: Raise. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Raise.
- Apply Raise in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Custom exceptions
EXCEPTION HANDLING: 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.
6 curriculum topics: Imports, Packages, Init.py, Virtual environments, Pip, Dependency management.
Imports
PYTHON MODULES & PACKAGES: Imports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Imports.
- Apply Imports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Packages
PYTHON MODULES & PACKAGES: Packages. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Packages.
- Apply Packages in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Init.py
PYTHON MODULES & PACKAGES: Init.py. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Init.py.
- Apply Init.py in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Virtual environments
PYTHON MODULES & PACKAGES: Virtual environments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Virtual environments.
- Apply Virtual environments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pip
PYTHON MODULES & PACKAGES: Pip. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pip.
- Apply Pip in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency management
PYTHON MODULES & PACKAGES: Dependency management. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency management.
- Apply Dependency management in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Text, CSV, JSON, Files, Directories.
Text
FILE & DATA HANDLING: Text. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Text.
- Apply Text in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSV
FILE & DATA HANDLING: 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.
JSON
FILE & DATA HANDLING: 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.
Files
FILE & DATA HANDLING: 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.
Directories
FILE & DATA HANDLING: Directories. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Directories.
- Apply Directories in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: DEBUG, INFO, WARNING, ERROR, CRITICAL, Structured logs, Passwords, Access tokens and 1 more topics.
DEBUG
LOGGING: DEBUG. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DEBUG.
- Apply DEBUG in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
INFO
LOGGING: INFO. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of INFO.
- Apply INFO in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
WARNING
LOGGING: WARNING. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of WARNING.
- Apply WARNING in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ERROR
LOGGING: ERROR. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ERROR.
- Apply ERROR in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CRITICAL
LOGGING: CRITICAL. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CRITICAL.
- Apply CRITICAL in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Structured logs
LOGGING: Structured logs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Structured logs.
- Apply Structured logs 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.
Access tokens
LOGGING: 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.
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.
4 curriculum topics: Threads, Processes, Asyncio, Async/await.
Threads
PYTHON CONCURRENCY: Threads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Threads.
- Apply Threads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Processes
PYTHON CONCURRENCY: 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.
Asyncio
PYTHON CONCURRENCY: Asyncio. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Asyncio.
- Apply Asyncio in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async/await
PYTHON CONCURRENCY: Async/await. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async/await.
- Apply Async/await in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: SELECT, INSERT, UPDATE, DELETE, WHERE, ORDER BY, GROUP BY, HAVING.
SELECT
SQL FUNDAMENTALS: 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 FUNDAMENTALS: 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 FUNDAMENTALS: 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 FUNDAMENTALS: 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.
WHERE
SQL FUNDAMENTALS: WHERE. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of WHERE.
- Apply WHERE in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ORDER BY
SQL FUNDAMENTALS: ORDER BY. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ORDER BY.
- Apply ORDER BY in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
GROUP BY
SQL FUNDAMENTALS: 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 FUNDAMENTALS: 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.
5 curriculum topics: INNER JOIN, LEFT JOIN, RIGHT JOIN concepts, Self joins, Multi-table queries.
INNER JOIN
SQL JOINS: INNER JOIN. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of INNER JOIN.
- Apply INNER JOIN in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
LEFT JOIN
SQL JOINS: LEFT JOIN. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of LEFT JOIN.
- Apply LEFT JOIN in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RIGHT JOIN concepts
SQL JOINS: RIGHT JOIN concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of RIGHT JOIN concepts.
- Apply RIGHT JOIN concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Self joins
SQL JOINS: Self joins. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Self joins.
- Apply Self joins in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-table queries
SQL JOINS: Multi-table queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Multi-table queries.
- Apply Multi-table queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Subqueries, CTE, CASE, Window functions, Transactions, Indexes, Query optimization.
Subqueries
ADVANCED 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.
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.
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.
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.
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.
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: Schemas, Tables, Constraints, Primary/foreign keys, Indexing, Transactions, Isolation concepts, JSONB concepts and 1 more topics.
Schemas
POSTGRESQL: Schemas. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schemas.
- Apply Schemas in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tables
POSTGRESQL: 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.
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.
Primary/foreign keys
POSTGRESQL: Primary/foreign keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Primary/foreign keys.
- Apply Primary/foreign keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexing
POSTGRESQL: Indexing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Indexing.
- Apply Indexing 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.
Isolation concepts
POSTGRESQL: Isolation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Isolation concepts.
- Apply Isolation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
JSONB concepts
POSTGRESQL: JSONB concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JSONB concepts.
- Apply JSONB concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query plans
POSTGRESQL: Query plans. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query plans.
- Apply Query plans in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: ER diagrams, Entities, Relationships, Normalization, One-to-one, One-to-many, Many-to-many.
ER diagrams
DATABASE MODELING: ER diagrams. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ER diagrams.
- Apply ER diagrams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Entities
DATABASE MODELING: Entities. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Entities.
- Apply Entities in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Relationships
DATABASE MODELING: 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.
Normalization
DATABASE MODELING: Normalization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Normalization.
- Apply Normalization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
One-to-one
DATABASE MODELING: One-to-one. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of One-to-one.
- Apply One-to-one in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
One-to-many
DATABASE MODELING: One-to-many. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of One-to-many.
- Apply One-to-many in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Many-to-many
DATABASE MODELING: Many-to-many. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Many-to-many.
- Apply Many-to-many in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Project, App, Settings, URLs, Views, Templates, Models.
Project
DJANGO FUNDAMENTALS: Project. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Project.
- Apply Project in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
App
DJANGO FUNDAMENTALS: App. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of App.
- Apply App in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Settings
DJANGO FUNDAMENTALS: Settings. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Settings.
- Apply Settings in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
URLs
DJANGO FUNDAMENTALS: URLs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of URLs.
- Apply URLs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Views
DJANGO FUNDAMENTALS: 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.
Templates
DJANGO FUNDAMENTALS: Templates. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Templates.
- Apply Templates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Models
DJANGO FUNDAMENTALS: 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.
9 curriculum topics: Models, QuerySets, Filtering, Aggregation, Relationships, Transactions, Indexes, Select_related and 1 more topics.
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.
Filtering
DJANGO ORM: 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.
Aggregation
DJANGO ORM: Aggregation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Aggregation.
- Apply Aggregation 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.
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.
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.
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.
6 curriculum topics: Model registration, List views, Filtering, Search, Permissions, Admin customization.
Model registration
DJANGO ADMIN: Model registration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Model registration.
- Apply Model registration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
List views
DJANGO ADMIN: List views. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of List views.
- Apply List views in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Filtering
DJANGO ADMIN: 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
DJANGO ADMIN: 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.
Permissions
DJANGO ADMIN: 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.
Admin customization
DJANGO ADMIN: Admin customization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Admin customization.
- Apply Admin customization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Users, Passwords, Sessions, Authentication, Permissions, Groups.
Users
DJANGO AUTHENTICATION: 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.
Passwords
DJANGO AUTHENTICATION: 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.
Sessions
DJANGO AUTHENTICATION: 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.
Authentication
DJANGO AUTHENTICATION: 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 AUTHENTICATION: 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.
Groups
DJANGO AUTHENTICATION: Groups. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Groups.
- Apply Groups in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Django Middleware.
Django Middleware
Understand request pipeline:; Request → Middleware → View → Middleware → Response
- Explain the core concepts and architecture of Django Middleware.
- Apply Django Middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
12 curriculum topics: Serializers concepts, Views, Routers concepts, Validation, Authentication, Permissions, Pagination, Student and 4 more topics.
Serializers concepts
DJANGO REST APIs: Serializers concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Serializers concepts.
- Apply Serializers concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Views
DJANGO REST APIs: 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.
Routers concepts
DJANGO REST APIs: Routers concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routers concepts.
- Apply Routers concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
DJANGO REST 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.
Authentication
DJANGO REST APIs: 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 APIs: 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 APIs: 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.
Student
DJANGO REST APIs: Student. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Student.
- Apply Student in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Trainer
DJANGO REST APIs: Trainer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Trainer.
- Apply Trainer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Courses
DJANGO REST APIs: Courses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Courses.
- Apply Courses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Enrollment
DJANGO REST APIs: Enrollment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Enrollment.
- Apply Enrollment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Admin
DJANGO REST APIs: 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.
6 curriculum topics: FastAPI application, Path operations, Path params, Query params, Request bodies, Response models.
FastAPI application
FASTAPI FUNDAMENTALS: FastAPI application. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of FastAPI application.
- Apply FastAPI application 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 params
FASTAPI FUNDAMENTALS: Path params. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Path params.
- Apply Path params in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query params
FASTAPI FUNDAMENTALS: Query params. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query params.
- Apply Query params 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.
Response models
FASTAPI FUNDAMENTALS: Response models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
6 curriculum topics: BaseModel, Validation, Nested models, Custom validators, Serialization, Configuration.
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.
Validation
PYDANTIC: 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.
Nested models
PYDANTIC: Nested models. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Nested models.
- Apply Nested models in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Custom validators
PYDANTIC: Custom validators. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Custom validators.
- Apply Custom validators 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.
Configuration
PYDANTIC: Configuration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Configuration.
- Apply Configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: DTOs, Status codes, Validation, Error handling.
DTOs
FASTAPI API DESIGN: DTOs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DTOs.
- Apply DTOs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status codes
FASTAPI API DESIGN: 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.
Validation
FASTAPI API 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.
Error handling
FASTAPI API DESIGN: Error handling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
4 curriculum topics: Dependencies, Database sessions, Authentication dependencies, Reusable validation.
Dependencies
FASTAPI DEPENDENCY INJECTION: Dependencies. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependencies.
- Apply Dependencies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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 dependencies
FASTAPI DEPENDENCY INJECTION: Authentication dependencies. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication dependencies.
- Apply Authentication dependencies in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reusable validation
FASTAPI DEPENDENCY INJECTION: Reusable validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reusable validation.
- Apply Reusable validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Synchronous functions, Asynchronous endpoints, Async database concepts, External APIs, Concurrent requests.
Synchronous functions
FASTAPI ASYNC: Synchronous functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Synchronous functions.
- Apply Synchronous functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Asynchronous endpoints
FASTAPI ASYNC: Asynchronous endpoints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Asynchronous endpoints.
- Apply Asynchronous endpoints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async database concepts
FASTAPI ASYNC: Async database concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async database concepts.
- Apply Async database concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
External APIs
FASTAPI ASYNC: 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.
Concurrent requests
FASTAPI ASYNC: Concurrent requests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Concurrent requests.
- Apply Concurrent requests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: ORM concepts, Models, Sessions, Relationships, Transactions, Querying.
ORM concepts
SQLALCHEMY: ORM concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ORM concepts.
- Apply ORM concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Models
SQLALCHEMY: 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.
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.
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.
Querying
SQLALCHEMY: Querying. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Querying.
- Apply Querying in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Schema versioning, Alembic concepts, Forward migrations, Rollback strategy.
Schema versioning
DATABASE MIGRATION: 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.
Alembic concepts
DATABASE MIGRATION: Alembic concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Alembic concepts.
- Apply Alembic concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Forward migrations
DATABASE MIGRATION: Forward migrations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Forward migrations.
- Apply Forward migrations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollback strategy
DATABASE MIGRATION: Rollback strategy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rollback strategy.
- Apply Rollback strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Resource modeling, Pagination, Sorting, Filtering, Search, Versioning, Error responses, Idempotency and 1 more topics.
Resource modeling
PRODUCTION REST API DESIGN: Resource modeling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Resource modeling.
- Apply Resource modeling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
PRODUCTION REST API DESIGN: 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.
Sorting
PRODUCTION REST API DESIGN: 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.
Filtering
PRODUCTION REST API DESIGN: 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
PRODUCTION REST API DESIGN: 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.
Versioning
PRODUCTION REST API DESIGN: Versioning. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Versioning.
- Apply Versioning in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error responses
PRODUCTION REST API DESIGN: Error responses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error responses.
- Apply Error responses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
PRODUCTION REST API 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.
API documentation
PRODUCTION REST API DESIGN: API documentation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API documentation.
- Apply API documentation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Customers, Products, Categories, Cart, Orders, Search, Pagination, PostgreSQL.
Customers
OPENAPI / SWAGGER: Customers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Customers.
- Apply Customers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Products
OPENAPI / SWAGGER: Products. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Products.
- Apply Products in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Categories
OPENAPI / SWAGGER: Categories. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Categories.
- Apply Categories in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cart
OPENAPI / SWAGGER: Cart. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cart.
- Apply Cart in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Orders
OPENAPI / SWAGGER: Orders. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Orders.
- Apply Orders in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Search
OPENAPI / SWAGGER: 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.
Pagination
OPENAPI / SWAGGER: 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.
PostgreSQL
OPENAPI / SWAGGER: 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.
4 curriculum topics: Session Authentication, Token Authentication, JWT, OAuth2.
Session Authentication
AUTHENTICATION: Session Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Session Authentication.
- Apply Session Authentication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token Authentication
AUTHENTICATION: Token Authentication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token Authentication.
- Apply Token Authentication 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.
6 curriculum topics: Access token, Refresh token, Expiry, Signatures, Token validation, Logout/revocation concepts.
Access token
JWT: Access token. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Access token.
- Apply Access token in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Refresh token
JWT: Refresh token. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Refresh token.
- Apply Refresh token 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.
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.
Token validation
JWT: Token validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token validation.
- Apply Token validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logout/revocation concepts
JWT: Logout/revocation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logout/revocation concepts.
- Apply Logout/revocation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rbac.
Rbac
Roles:; USER; MANAGER; ADMIN; Enforce backend authorization.
- 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.
5 curriculum topics: Authorization code, PKCE, Client credentials, Scopes, External identity providers.
Authorization code
OAUTH2 / OIDC: 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 / OIDC: 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 / OIDC: 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 / OIDC: 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.
External identity providers
OAUTH2 / OIDC: External identity providers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of External identity providers.
- Apply External identity providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: SQL injection, XSS, CSRF, CORS, Broken access control, Password hashing, Secure cookies, Secrets and 2 more topics.
SQL injection
WEB 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.
XSS
WEB SECURITY: XSS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of XSS.
- Apply XSS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CSRF
WEB 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.
CORS
WEB 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.
Broken access control
WEB SECURITY: Broken access control. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Broken access control.
- Apply Broken access control in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Password hashing
WEB 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
WEB 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.
Secrets
WEB SECURITY: 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.
Rate limiting
WEB 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.
File upload security
WEB SECURITY: File upload security. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File upload security.
- Apply File upload security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Caching, TTL, Invalidation, Sessions, Rate-limiting concepts.
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.
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.
Sessions
REDIS: 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.
Rate-limiting concepts
REDIS: Rate-limiting concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate-limiting concepts.
- Apply Rate-limiting concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Long-running tasks, Workers, Queues, Retries, Scheduled jobs, Celery concepts.
Long-running tasks
BACKGROUND JOBS: Long-running tasks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Long-running tasks.
- Apply Long-running tasks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Workers
BACKGROUND JOBS: Workers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Workers.
- Apply Workers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queues
BACKGROUND JOBS: 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.
Retries
BACKGROUND JOBS: 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.
Scheduled jobs
BACKGROUND JOBS: Scheduled jobs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scheduled jobs.
- Apply Scheduled jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Celery concepts
BACKGROUND JOBS: Celery concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Celery concepts.
- Apply Celery concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Verification emails, Reset password emails, Notifications.
Verification emails
EMAIL & NOTIFICATION SERVICES: Verification emails. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Verification emails.
- Apply Verification emails in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reset password emails
EMAIL & NOTIFICATION SERVICES: Reset password emails. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reset password emails.
- Apply Reset password emails in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
EMAIL & NOTIFICATION SERVICES: 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.
5 curriculum topics: File validation, File size, MIME type, Local storage, Object storage.
File validation
FILE UPLOADS: File validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File validation.
- Apply File validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File size
FILE UPLOADS: File size. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File size.
- Apply File size in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
MIME type
FILE UPLOADS: 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.
Local storage
FILE UPLOADS: Local storage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Local storage.
- Apply Local storage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Object storage
FILE UPLOADS: Object storage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Object storage.
- Apply Object storage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Profile images, Documents, Exports.
Profile images
AWS S3 INTEGRATION: Profile images. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Profile images.
- Apply Profile images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Documents
AWS S3 INTEGRATION: 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.
Exports
AWS S3 INTEGRATION: 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.
3 curriculum topics: Chat, Notifications, Job status.
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.
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.
Job status
WEBSOCKETS: Job status. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Job status.
- Apply Job status in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: AI responses, Background process status.
AI responses
SERVER-SENT EVENTS: AI responses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI responses.
- Apply AI responses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Background process status
SERVER-SENT EVENTS: Background process status. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Background process status.
- Apply Background process status in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Modular monolith, Service boundaries, Independent deployment, Database ownership.
Modular monolith
MICROSERVICES FUNDAMENTALS: Modular monolith. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Modular monolith.
- Apply Modular monolith in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service boundaries
MICROSERVICES FUNDAMENTALS: 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.
Independent deployment
MICROSERVICES FUNDAMENTALS: 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 FUNDAMENTALS: 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: Fastapi Microservices.
Fastapi Microservices
Design:; identity-service; course-service; payment-service; notification-service
- Explain the core concepts and architecture of Fastapi Microservices.
- Apply Fastapi Microservices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: REST, Events concepts, Timeouts, Retries, Idempotency.
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 concepts
SERVICE COMMUNICATION: Events concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Events concepts.
- Apply Events concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timeouts
SERVICE COMMUNICATION: Timeouts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
Retries
SERVICE COMMUNICATION: 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
SERVICE COMMUNICATION: 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: Kafka concepts, RabbitMQ concepts, Producer, Consumer, Events.
Kafka concepts
EVENT-DRIVEN SYSTEMS: 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.
RabbitMQ concepts
EVENT-DRIVEN SYSTEMS: RabbitMQ concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of RabbitMQ concepts.
- Apply RabbitMQ concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Producer
EVENT-DRIVEN SYSTEMS: 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
EVENT-DRIVEN SYSTEMS: 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.
Events
EVENT-DRIVEN SYSTEMS: 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.
8 curriculum topics: Primitives, Arrays, Interfaces, Type aliases, Union, Generics, Utility types, API types.
Primitives
TYPESCRIPT: Primitives. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Primitives.
- Apply Primitives in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Arrays
TYPESCRIPT: Arrays. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Arrays.
- Apply Arrays in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Interfaces
TYPESCRIPT: Interfaces. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Interfaces.
- Apply Interfaces in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Type aliases
TYPESCRIPT: Type aliases. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Type aliases.
- Apply Type aliases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Union
TYPESCRIPT: 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.
Generics
TYPESCRIPT: 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.
Utility types
TYPESCRIPT: Utility types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Utility types.
- Apply Utility types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API types
TYPESCRIPT: API types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API types.
- Apply API types in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: JSX, Components, Props, State, Events, Conditional rendering, Lists.
JSX
REACT FUNDAMENTALS: JSX. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of JSX.
- Apply JSX in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Components
REACT FUNDAMENTALS: Components. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Components.
- Apply Components in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Props
REACT FUNDAMENTALS: Props. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Props.
- Apply Props in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
State
REACT FUNDAMENTALS: State. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of State.
- Apply State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
REACT FUNDAMENTALS: 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.
Conditional rendering
REACT FUNDAMENTALS: Conditional rendering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Conditional rendering.
- Apply Conditional rendering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lists
REACT FUNDAMENTALS: Lists. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lists.
- Apply Lists in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: UseState, UseEffect, UseRef, UseMemo, UseCallback, Context, Custom hooks.
UseState
REACT HOOKS: UseState. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseState.
- Apply UseState in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UseEffect
REACT HOOKS: UseEffect. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseEffect.
- Apply UseEffect in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UseRef
REACT HOOKS: UseRef. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseRef.
- Apply UseRef in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UseMemo
REACT HOOKS: UseMemo. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseMemo.
- Apply UseMemo in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
UseCallback
REACT HOOKS: UseCallback. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseCallback.
- Apply UseCallback in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context
REACT HOOKS: 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.
Custom hooks
REACT HOOKS: Custom hooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Custom hooks.
- Apply Custom hooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Router, Routes, Protected routes, Nested routes, Dynamic routes.
Router
REACT ROUTING: Router. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Router.
- Apply Router in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routes
REACT ROUTING: Routes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routes.
- Apply Routes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Protected routes
REACT ROUTING: Protected routes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Protected routes.
- Apply Protected routes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Nested routes
REACT ROUTING: Nested routes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Nested routes.
- Apply Nested routes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dynamic routes
REACT ROUTING: Dynamic routes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dynamic routes.
- Apply Dynamic routes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Controlled fields, Validation, Reusable forms, Error messages, Accessibility.
Controlled fields
REACT FORMS: Controlled fields. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Controlled fields.
- Apply Controlled fields in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
REACT FORMS: 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.
Reusable forms
REACT FORMS: Reusable forms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reusable forms.
- Apply Reusable forms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error messages
REACT FORMS: Error messages. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error messages.
- Apply Error messages in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Accessibility
REACT FORMS: Accessibility. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Accessibility.
- Apply Accessibility in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Component State, Context, Redux Toolkit concepts, Zustand concepts, Server State.
Component State
REACT STATE MANAGEMENT: Component State. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Component State.
- Apply Component State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context
REACT STATE MANAGEMENT: 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.
Redux Toolkit concepts
REACT STATE MANAGEMENT: Redux Toolkit concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redux Toolkit concepts.
- Apply Redux Toolkit concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Zustand concepts
REACT STATE MANAGEMENT: Zustand concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Zustand concepts.
- Apply Zustand concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Server State
REACT STATE MANAGEMENT: Server State. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Server State.
- Apply Server State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Fetching, Mutation, Loading, Errors, Pagination, Filtering, Authentication.
Fetching
REACT API INTEGRATION: Fetching. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fetching.
- Apply Fetching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mutation
REACT API INTEGRATION: Mutation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mutation.
- Apply Mutation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Loading
REACT API INTEGRATION: Loading. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Loading.
- Apply Loading in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
REACT API INTEGRATION: 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.
Pagination
REACT API INTEGRATION: 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
REACT API INTEGRATION: 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.
Authentication
REACT API INTEGRATION: 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.
5 curriculum topics: Login, Logout, Protected routes, User profile, Role-based UI.
Login
REACT AUTHENTICATION: Login. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Login.
- Apply Login in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logout
REACT AUTHENTICATION: Logout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Logout.
- Apply Logout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Protected routes
REACT AUTHENTICATION: Protected routes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Protected routes.
- Apply Protected routes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
User profile
REACT AUTHENTICATION: User profile. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of User profile.
- Apply User profile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Role-based UI
REACT AUTHENTICATION: Role-based UI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Role-based UI.
- Apply Role-based UI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: XSS awareness, Token-storage risks, Secure cookies, Sanitization, Dependency security.
XSS awareness
FRONTEND 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.
Token-storage risks
FRONTEND SECURITY: Token-storage risks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token-storage risks.
- Apply Token-storage risks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secure cookies
FRONTEND 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.
Sanitization
FRONTEND SECURITY: Sanitization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sanitization.
- Apply Sanitization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency security
FRONTEND SECURITY: Dependency security. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency security.
- Apply Dependency security in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Rerendering, Memoization, Lazy loading, Code splitting, Bundle optimization.
Rerendering
REACT PERFORMANCE: Rerendering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rerendering.
- Apply Rerendering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Memoization
REACT PERFORMANCE: Memoization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Memoization.
- Apply Memoization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lazy loading
REACT PERFORMANCE: Lazy loading. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lazy loading.
- Apply Lazy loading in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Code splitting
REACT PERFORMANCE: Code splitting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Code splitting.
- Apply Code splitting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bundle optimization
REACT PERFORMANCE: Bundle optimization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Bundle optimization.
- Apply Bundle optimization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Desktop, Tablet, Android, IPhone.
Desktop
RESPONSIVE UX: Desktop. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Desktop.
- Apply Desktop in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tablet
RESPONSIVE UX: Tablet. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tablet.
- Apply Tablet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Android
RESPONSIVE UX: Android. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Android.
- Apply Android in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
IPhone
RESPONSIVE UX: IPhone. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of IPhone.
- Apply IPhone in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
13 curriculum topics: Semantic elements, Labels, Keyboard navigation, Contrast, Accessible forms, Registration, Login, Dashboard and 5 more topics.
Semantic elements
ACCESSIBILITY: Semantic elements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Semantic elements.
- Apply Semantic elements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Labels
ACCESSIBILITY: Labels. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Labels.
- Apply Labels in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keyboard navigation
ACCESSIBILITY: Keyboard navigation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Keyboard navigation.
- Apply Keyboard navigation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Contrast
ACCESSIBILITY: Contrast. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Contrast.
- Apply Contrast in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Accessible forms
ACCESSIBILITY: Accessible forms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Accessible forms.
- Apply Accessible forms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Registration
ACCESSIBILITY: Registration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Registration.
- Apply Registration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Login
ACCESSIBILITY: Login. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Login.
- Apply Login in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dashboard
ACCESSIBILITY: Dashboard. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dashboard.
- Apply Dashboard in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Employees
ACCESSIBILITY: Employees. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Employees.
- Apply Employees in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Departments
ACCESSIBILITY: Departments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Departments.
- Apply Departments in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
ACCESSIBILITY: 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.
Search
ACCESSIBILITY: 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.
RBAC
ACCESSIBILITY: RBAC. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
9 curriculum topics: Full web platform, Built-in admin, Authentication-heavy business applications, ORM-centric systems, APIs, Microservices, Async integrations, AI services and 1 more topics.
Full web platform
DJANGO VS FASTAPI: Full web platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Full web platform.
- Apply Full web platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Built-in admin
DJANGO VS FASTAPI: Built-in admin. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Built-in admin.
- Apply Built-in admin in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication-heavy business applications
DJANGO VS FASTAPI: Authentication-heavy business applications. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication-heavy business applications.
- Apply Authentication-heavy business applications in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ORM-centric systems
DJANGO VS FASTAPI: ORM-centric systems. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ORM-centric systems.
- Apply ORM-centric systems in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
APIs
DJANGO VS FASTAPI: 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.
Microservices
DJANGO VS FASTAPI: 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.
Async integrations
DJANGO VS FASTAPI: Async integrations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async integrations.
- Apply Async integrations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI services
DJANGO VS FASTAPI: AI services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI services.
- Apply AI services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Typed backend services
DJANGO VS FASTAPI: Typed backend services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Typed backend services.
- Apply Typed backend services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: React framework architecture, Routing, Server/client components awareness, SSR concepts, Python API integration.
React framework architecture
NEXT.JS AWARENESS: React framework architecture. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of React framework architecture.
- Apply React framework architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routing
NEXT.JS AWARENESS: Routing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routing.
- Apply Routing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Server/client components awareness
NEXT.JS AWARENESS: Server/client components awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Server/client components awareness.
- Apply Server/client components awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SSR concepts
NEXT.JS AWARENESS: SSR concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SSR concepts.
- Apply SSR concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Python API integration
NEXT.JS AWARENESS: Python API integration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Python API integration.
- Apply Python API integration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Pytest, Unittest concepts, Fixtures, Mocking, Parameterized tests.
Pytest
BACKEND TESTING: Pytest. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pytest.
- Apply Pytest in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unittest concepts
BACKEND TESTING: Unittest concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unittest concepts.
- Apply Unittest concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fixtures
BACKEND TESTING: 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.
Mocking
BACKEND TESTING: Mocking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mocking.
- Apply Mocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Parameterized tests
BACKEND TESTING: Parameterized tests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Parameterized tests.
- Apply Parameterized tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Endpoints, Validation, Authentication, Permissions, Database interactions.
Endpoints
FASTAPI TESTING: Endpoints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Endpoints.
- Apply Endpoints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
Authentication
FASTAPI TESTING: 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
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 interactions
FASTAPI TESTING: Database interactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database interactions.
- Apply Database interactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Models, Views, Authentication, Permissions.
Models
DJANGO TESTING: 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.
Views
DJANGO TESTING: 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.
Authentication
DJANGO TESTING: 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 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.
3 curriculum topics: React Testing Library concepts, Component tests, Interaction tests.
React Testing Library concepts
FRONTEND TESTING: React Testing Library concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of React Testing Library concepts.
- Apply React Testing Library concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Component tests
FRONTEND TESTING: Component tests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Component tests.
- Apply Component tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Interaction tests
FRONTEND TESTING: Interaction tests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Interaction tests.
- Apply Interaction tests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Playwright concepts, Browser automation.
Playwright concepts
END-TO-END TESTING: Playwright concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Playwright concepts.
- Apply Playwright concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Browser automation
END-TO-END TESTING: Browser automation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Browser automation.
- Apply Browser automation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Postman, Automated collections, Environments.
Postman
API TESTING: Postman. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Postman.
- Apply Postman in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Automated collections
API TESTING: Automated collections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Automated collections.
- Apply Automated collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environments
API TESTING: Environments. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
7 curriculum topics: Repositories, Commits, Branches, Merge, Conflicts, Pull requests, Code review.
Repositories
GIT: Repositories. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Repositories.
- Apply Repositories in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Commits
GIT: Commits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Commits.
- Apply Commits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Branches
GIT: Branches. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Branches.
- Apply Branches in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Merge
GIT: Merge. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Merge.
- Apply Merge in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conflicts
GIT: Conflicts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Conflicts.
- Apply Conflicts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pull requests
GIT: Pull requests. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Pull requests.
- Apply Pull requests in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Code review
GIT: Code review. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Code review.
- Apply Code review in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Naming, Separation of concerns, SOLID, DRY, KISS, Maintainability.
Naming
CLEAN CODE: Naming. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Naming.
- Apply Naming in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Separation of concerns
CLEAN CODE: Separation of concerns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Separation of concerns.
- Apply Separation of concerns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SOLID
CLEAN CODE: SOLID. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SOLID.
- Apply SOLID in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DRY
CLEAN CODE: DRY. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DRY.
- Apply DRY in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
KISS
CLEAN CODE: KISS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of KISS.
- Apply KISS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Maintainability
CLEAN CODE: Maintainability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Maintainability.
- Apply Maintainability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Factory, Strategy, Adapter, Repository, Service, Observer, Dependency Injection.
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.
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.
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.
1 curriculum topics: Backend Architecture.
Backend Architecture
Teach:; Layered Architecture; Clean Architecture concepts; Hexagonal Architecture concepts; Domain-oriented architecture
- Explain the core concepts and architecture of Backend Architecture.
- Apply Backend Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Images, Containers, Dockerfile, Multi-stage builds, Networks, 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 builds
DOCKER: Multi-stage builds. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Multi-stage builds.
- Apply Multi-stage builds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Networks
DOCKER: Networks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Networks.
- Apply Networks 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 stack:; React; *; FastAPI; PostgreSQL; Redis
- 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.
1 curriculum topics: Ci/Cd.
Ci/Cd
Pipeline:; Commit; Lint; Tests; Build; Docker; 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
Students create an automated build/test 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.
6 curriculum topics: IAM, EC2, S3, RDS, Networking, CloudWatch.
IAM
AWS FUNDAMENTALS: IAM. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of IAM.
- Apply IAM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
EC2
AWS FUNDAMENTALS: EC2. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
S3
AWS FUNDAMENTALS: S3. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
RDS
AWS FUNDAMENTALS: RDS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
Networking
AWS FUNDAMENTALS: 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.
CloudWatch
AWS FUNDAMENTALS: CloudWatch. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CloudWatch.
- Apply CloudWatch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Frontend, Python API, PostgreSQL, Storage.
Frontend
AWS DEPLOYMENT: Frontend. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Frontend.
- Apply Frontend in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Python API
AWS DEPLOYMENT: Python API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Python API.
- Apply Python API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PostgreSQL
AWS DEPLOYMENT: 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.
Storage
AWS DEPLOYMENT: 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.
2 curriculum topics: AWS Lambda, API Gateway concepts.
AWS Lambda
SERVERLESS AWARENESS: AWS Lambda. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- 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.
API Gateway concepts
SERVERLESS AWARENESS: API Gateway concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API Gateway concepts.
- Apply API Gateway concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Pods, Deployments, Services, ConfigMaps, Secrets, Health probes, Scaling.
Pods
KUBERNETES AWARENESS: 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 AWARENESS: 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 AWARENESS: 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 AWARENESS: 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 AWARENESS: 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 AWARENESS: 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 AWARENESS: 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.
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.
5 curriculum topics: Request ID, User, Endpoint, Duration, Error.
Request ID
STRUCTURED LOGGING: Request ID. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Request ID.
- Apply Request ID in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
User
STRUCTURED LOGGING: User. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of User.
- Apply User in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Endpoint
STRUCTURED LOGGING: Endpoint. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Endpoint.
- Apply Endpoint in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duration
STRUCTURED LOGGING: Duration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Duration.
- Apply Duration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error
STRUCTURED LOGGING: Error. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error.
- Apply Error in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Requests, Errors, Latency, CPU, Memory, Database pool.
Requests
APPLICATION 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
APPLICATION 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
APPLICATION 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.
CPU
APPLICATION METRICS: 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.
Memory
APPLICATION METRICS: Memory. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Memory.
- Apply Memory in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database pool
APPLICATION METRICS: Database pool. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database pool.
- Apply Database pool in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Database, External API, Event loop blocking, Connection pool, Network.
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.
External API
PRODUCTION DEBUGGING: External API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of External API.
- Apply External API 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.
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.
Network
PRODUCTION DEBUGGING: Network. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Network.
- Apply Network in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Indexes, N+1, Pagination, Query optimization, Connection pooling.
Indexes
DATABASE PERFORMANCE: 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.
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.
Pagination
DATABASE PERFORMANCE: 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.
Query optimization
DATABASE PERFORMANCE: 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.
Connection pooling
DATABASE PERFORMANCE: Connection pooling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection pooling.
- Apply Connection pooling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Cache hit, Cache miss, TTL, Invalidation, Cache stampede concepts.
Cache hit
CACHING PERFORMANCE: 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
CACHING PERFORMANCE: 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.
TTL
CACHING PERFORMANCE: 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.
Invalidation
CACHING PERFORMANCE: 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.
Cache stampede concepts
CACHING PERFORMANCE: Cache stampede concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache stampede concepts.
- Apply Cache stampede concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Dependency updates, Secret rotation, Audit logging, TLS, Least privilege, Vulnerability remediation.
Dependency updates
APPLICATION SECURITY OPERATIONS: Dependency updates. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency updates.
- Apply Dependency updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secret rotation
APPLICATION SECURITY OPERATIONS: Secret rotation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secret rotation.
- Apply Secret rotation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Audit logging
APPLICATION SECURITY OPERATIONS: Audit logging. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Audit logging.
- Apply Audit logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TLS
APPLICATION SECURITY OPERATIONS: TLS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of TLS.
- Apply TLS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Least privilege
APPLICATION SECURITY OPERATIONS: Least privilege. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Least privilege.
- Apply Least privilege in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Vulnerability remediation
APPLICATION SECURITY OPERATIONS: Vulnerability remediation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Vulnerability remediation.
- Apply Vulnerability remediation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: Functional Requirements, Non-Functional Requirements, API Design, Database, Cache, Storage, Queue, Scaling and 2 more topics.
Functional Requirements
SYSTEM DESIGN: Functional Requirements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Functional Requirements.
- Apply Functional Requirements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Non-Functional Requirements
SYSTEM DESIGN: Non-Functional Requirements. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Non-Functional Requirements.
- Apply Non-Functional Requirements in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API Design
SYSTEM DESIGN: API Design. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API Design.
- Apply API Design 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.
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.
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.
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.
7 curriculum topics: LLM APIs, Prompt Fundamentals, Streaming, Structured Output, Tool Calling Concepts, Embeddings Concepts, RAG Fundamentals.
LLM APIs
GENAI FOR PYTHON FULL STACK: 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.
Prompt Fundamentals
GENAI FOR PYTHON FULL STACK: Prompt Fundamentals. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prompt Fundamentals.
- Apply Prompt Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
GENAI FOR PYTHON FULL STACK: 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
GENAI FOR PYTHON FULL STACK: 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 Calling Concepts
GENAI FOR PYTHON FULL STACK: Tool Calling Concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tool Calling Concepts.
- Apply Tool Calling Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embeddings Concepts
GENAI FOR PYTHON FULL STACK: Embeddings Concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Embeddings Concepts.
- Apply Embeddings Concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RAG Fundamentals
GENAI FOR PYTHON FULL STACK: 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.
6 curriculum topics: Prompt injection, Unauthorized data access, Token cost, Output validation, Secrets, Rate limiting.
Prompt injection
AI SECURITY: Prompt injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prompt injection.
- Apply Prompt injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unauthorized data access
AI SECURITY: Unauthorized data access. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unauthorized data access.
- Apply Unauthorized data access in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token cost
AI SECURITY: Token cost. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token cost.
- Apply Token cost in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Output validation
AI 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.
Secrets
AI SECURITY: 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.
Rate limiting
AI 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.
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.
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