MERN 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 MERN 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
110 Modules • 571 Deep-Dive Topics • 571 Integrated Topic Mock Tests & AI Interviews
4 curriculum topics: How the Internet Works, Client/Server Architecture, HTTP Fundamentals, Status Codes.
How the Internet Works
Understand:; Browser; server; DNS; domain; IP; TCP concepts; HTTP; HTTPS
- Explain the core concepts and architecture of How the Internet Works.
- Apply How the Internet Works in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Client/Server Architecture
Architecture:; Browser → API → Backend → Database
- 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 Fundamentals
Methods:; GET; POST; PUT; PATCH; DELETE
- Explain the core concepts and architecture of HTTP Fundamentals.
- Apply HTTP Fundamentals in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Status Codes
Important:; 200; 201; 204; 400; 401; 403; 404; 409; 422; 429; 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.
11 curriculum topics: Document structure, Semantic HTML, Headings, Forms, Inputs, Buttons, Tables, Media and 3 more topics.
Document structure
HTML5: Document structure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Document structure.
- Apply Document structure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
Media
HTML5: Media. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Media.
- Apply Media 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.
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.
Metadata
HTML5: Metadata. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Metadata.
- Apply Metadata in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Selectors, Box model, Typography, Positioning, Flexbox, CSS Grid, Variables, Transitions 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.
Typography
CSS3: Typography. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Typography.
- Apply Typography 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.
Variables
CSS3: 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.
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.
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.
9 curriculum topics: Desktop, Tablet, Android, IPhone, Breakpoints, Mobile-first design, Responsive images, Fluid layout and 1 more topics.
Desktop
RESPONSIVE DESIGN: 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 DESIGN: 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 DESIGN: 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 DESIGN: 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.
Breakpoints
RESPONSIVE DESIGN: Breakpoints. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Breakpoints.
- Apply Breakpoints in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mobile-first design
RESPONSIVE DESIGN: Mobile-first design. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mobile-first design.
- Apply Mobile-first design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Responsive images
RESPONSIVE DESIGN: Responsive images. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Responsive images.
- Apply Responsive images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fluid layout
RESPONSIVE DESIGN: Fluid layout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fluid layout.
- Apply Fluid layout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Touch targets
RESPONSIVE DESIGN: Touch targets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Touch targets.
- Apply Touch targets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Variables, Let, Const, Primitive types, Objects, Operators, Conditions, 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
JAVASCRIPT FUNDAMENTALS: Let. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Let.
- Apply Let in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Const
JAVASCRIPT FUNDAMENTALS: Const. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Const.
- Apply Const in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Primitive types
JAVASCRIPT FUNDAMENTALS: Primitive types. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Primitive types.
- Apply Primitive types 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.
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.
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.
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.
12 curriculum topics: Arrays, Objects, Maps, Sets, Strings, Map, Filter, Reduce and 4 more topics.
Arrays
JAVASCRIPT DATA STRUCTURES: 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 DATA STRUCTURES: 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.
Maps
JAVASCRIPT DATA STRUCTURES: Maps. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Maps.
- Apply Maps in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sets
JAVASCRIPT DATA STRUCTURES: 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.
Strings
JAVASCRIPT DATA STRUCTURES: 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.
Map
JAVASCRIPT DATA STRUCTURES: Map. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Map.
- Apply Map in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Filter
JAVASCRIPT DATA STRUCTURES: Filter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filter.
- Apply Filter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reduce
JAVASCRIPT DATA STRUCTURES: Reduce. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reduce.
- Apply Reduce in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Find
JAVASCRIPT DATA STRUCTURES: Find. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Find.
- Apply Find in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Some
JAVASCRIPT DATA STRUCTURES: Some. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Some.
- Apply Some in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Every
JAVASCRIPT DATA STRUCTURES: Every. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Every.
- Apply Every in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sort
JAVASCRIPT DATA STRUCTURES: Sort. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sort.
- Apply Sort in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Declarations, Expressions, Arrow functions, Callbacks, Higher-order functions, Lexical scope.
Declarations
JAVASCRIPT FUNCTIONS: Declarations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Declarations.
- Apply Declarations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expressions
JAVASCRIPT FUNCTIONS: Expressions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Expressions.
- Apply Expressions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Arrow functions
JAVASCRIPT FUNCTIONS: 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.
Callbacks
JAVASCRIPT FUNCTIONS: 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.
Higher-order functions
JAVASCRIPT FUNCTIONS: Higher-order functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Higher-order functions.
- Apply Higher-order functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lexical scope
JAVASCRIPT FUNCTIONS: Lexical scope. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lexical scope.
- Apply Lexical scope in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Execution context, Call stack, Scope, Lexical environment, Hoisting, Closures, This, Prototype and 1 more topics.
Execution context
JAVASCRIPT INTERNALS: Execution context. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Execution context.
- Apply Execution context in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Call stack
JAVASCRIPT INTERNALS: Call stack. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Call stack.
- Apply Call stack in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scope
JAVASCRIPT INTERNALS: 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.
Lexical environment
JAVASCRIPT INTERNALS: Lexical environment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lexical environment.
- Apply Lexical environment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Hoisting
JAVASCRIPT INTERNALS: Hoisting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Hoisting.
- Apply Hoisting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Closures
JAVASCRIPT INTERNALS: 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.
This
JAVASCRIPT INTERNALS: This. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of This.
- Apply This in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prototype
JAVASCRIPT INTERNALS: Prototype. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prototype.
- Apply Prototype in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Prototype chain
JAVASCRIPT INTERNALS: Prototype chain. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prototype chain.
- Apply Prototype chain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Destructuring, Spread, Rest, Template literals, Optional chaining, Nullish coalescing, ES modules, Dynamic imports.
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
MODERN JAVASCRIPT: Spread. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Spread.
- Apply Spread in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rest
MODERN JAVASCRIPT: 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.
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.
ES modules
MODERN JAVASCRIPT: ES modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ES modules.
- Apply ES modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dynamic imports
MODERN JAVASCRIPT: Dynamic imports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dynamic imports.
- Apply Dynamic imports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Callback, Promise, Async, Await, Promise.all, Promise.allSettled, Error handling.
Callback
ASYNCHRONOUS JAVASCRIPT: Callback. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Callback.
- Apply Callback in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise
ASYNCHRONOUS JAVASCRIPT: Promise. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Promise.
- Apply Promise 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.
Promise.all
ASYNCHRONOUS JAVASCRIPT: Promise.all. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Promise.all.
- Apply Promise.all in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise.allSettled
ASYNCHRONOUS JAVASCRIPT: Promise.allSettled. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Promise.allSettled.
- Apply Promise.allSettled 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.
6 curriculum topics: Call stack, Task queue, Microtask queue, Promise callbacks, Timers, Node/browser differences conceptually.
Call stack
EVENT LOOP: Call stack. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Call stack.
- Apply Call stack in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Task queue
EVENT LOOP: Task queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Task queue.
- Apply Task queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Microtask queue
EVENT LOOP: Microtask queue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Microtask queue.
- Apply Microtask queue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promise callbacks
EVENT LOOP: Promise callbacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Promise callbacks.
- Apply Promise callbacks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timers
EVENT LOOP: Timers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Timers.
- Apply Timers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Node/browser differences conceptually
EVENT LOOP: Node/browser differences conceptually. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Node/browser differences conceptually.
- Apply Node/browser differences conceptually in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: DOM, Events, Forms, LocalStorage, SessionStorage, Fetch API, URL APIs.
DOM
BROWSER APIs: DOM. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DOM.
- Apply DOM in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
BROWSER APIs: 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.
Forms
BROWSER APIs: 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.
LocalStorage
BROWSER APIs: LocalStorage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of LocalStorage.
- Apply LocalStorage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SessionStorage
BROWSER APIs: SessionStorage. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SessionStorage.
- Apply SessionStorage in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Fetch API
BROWSER APIs: 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.
URL APIs
BROWSER APIs: URL APIs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of URL APIs.
- Apply URL APIs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Repository, Commits, Branches, Merges, Conflicts, Pull requests, Reviews, Tags.
Repository
GIT & GITHUB: 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.
Commits
GIT & GITHUB: 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 & GITHUB: 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.
Merges
GIT & GITHUB: Merges. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Merges.
- Apply Merges in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Conflicts
GIT & GITHUB: 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 & GITHUB: 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.
Reviews
GIT & GITHUB: Reviews. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reviews.
- Apply Reviews in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tags
GIT & GITHUB: Tags. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tags.
- Apply Tags in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Type annotations, Primitives, Arrays, Tuples, Enums awareness, Objects.
Type annotations
TYPESCRIPT FUNDAMENTALS: Type annotations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Type annotations.
- Apply Type annotations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Primitives
TYPESCRIPT FUNDAMENTALS: 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 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.
Tuples
TYPESCRIPT 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.
Enums awareness
TYPESCRIPT FUNDAMENTALS: Enums awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Enums awareness.
- Apply Enums awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Objects
TYPESCRIPT 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.
10 curriculum topics: Interfaces, Type aliases, Unions, Intersections, Generics, Utility types, Narrowing, Discriminated unions and 2 more topics.
Interfaces
ADVANCED 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
ADVANCED 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.
Unions
ADVANCED TYPESCRIPT: Unions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unions.
- Apply Unions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Intersections
ADVANCED TYPESCRIPT: Intersections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Intersections.
- Apply Intersections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Generics
ADVANCED 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
ADVANCED 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.
Narrowing
ADVANCED TYPESCRIPT: Narrowing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Narrowing.
- Apply Narrowing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Discriminated unions
ADVANCED TYPESCRIPT: Discriminated unions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Discriminated unions.
- Apply Discriminated unions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Keyof
ADVANCED TYPESCRIPT: Keyof. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Keyof.
- Apply Keyof in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Mapped types concepts
ADVANCED TYPESCRIPT: Mapped types concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Mapped types concepts.
- Apply Mapped types concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Typescript For Apis.
Typescript For Apis
Define:; text; UserRequest; UserResponse; OrderDTO; ApiError; PaginationResponse<T>; Teach end-to-end contracts.
- Explain the core concepts and architecture of Typescript For Apis.
- Apply Typescript For Apis in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: React architecture, JSX, Components, Props, State, Events, Conditional rendering, Lists and 1 more topics.
React architecture
REACT FUNDAMENTALS: React architecture. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of React architecture.
- Apply React architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
Keys
REACT FUNDAMENTALS: Keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Keys.
- Apply Keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: UseState, UseEffect, UseRef, UseMemo, UseCallback, UseContext, 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.
UseContext
REACT HOOKS: UseContext. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of UseContext.
- Apply UseContext 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: Presentational Components, Container concepts, Composition, Reusable Components, Controlled Components.
Presentational Components
REACT COMPONENT DESIGN: Presentational Components. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Presentational Components.
- Apply Presentational Components in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Container concepts
REACT COMPONENT DESIGN: Container concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Container concepts.
- Apply Container concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Composition
REACT COMPONENT DESIGN: 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.
Reusable Components
REACT COMPONENT DESIGN: Reusable Components. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reusable Components.
- Apply Reusable Components in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Controlled Components
REACT COMPONENT DESIGN: Controlled Components. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Controlled Components.
- Apply Controlled Components in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Routes, Dynamic routes, Nested routes, Protected routes, Layouts, Error boundaries/concepts.
Routes
REACT ROUTER: 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.
Dynamic routes
REACT ROUTER: 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.
Nested routes
REACT ROUTER: 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.
Protected routes
REACT ROUTER: 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.
Layouts
REACT ROUTER: Layouts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Layouts.
- Apply Layouts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error boundaries/concepts
REACT ROUTER: Error boundaries/concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error boundaries/concepts.
- Apply Error boundaries/concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Controlled forms, Validation, Touched/errors, Reusable fields, Schema validation concepts.
Controlled forms
FORMS: Controlled forms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Controlled forms.
- Apply Controlled forms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
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.
Touched/errors
FORMS: Touched/errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Touched/errors.
- Apply Touched/errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reusable fields
FORMS: Reusable fields. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reusable fields.
- Apply Reusable fields in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Schema validation concepts
FORMS: Schema validation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schema validation concepts.
- Apply Schema validation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Local State, Lifted State, Context, Redux Toolkit, Zustand concepts.
Local State
STATE MANAGEMENT: Local State. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Local State.
- Apply Local State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Lifted State
STATE MANAGEMENT: Lifted State. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Lifted State.
- Apply Lifted State in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context
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
STATE MANAGEMENT: Redux Toolkit. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redux Toolkit.
- Apply Redux Toolkit in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Zustand concepts
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.
4 curriculum topics: Caching, Invalidation, Refetching, Optimistic updates.
Caching
SERVER STATE: 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.
Invalidation
SERVER STATE: 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.
Refetching
SERVER STATE: Refetching. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Refetching.
- Apply Refetching in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Optimistic updates
SERVER STATE: Optimistic updates. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Optimistic updates.
- Apply Optimistic updates in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Fetch, Axios awareness, Loading, Errors, Retries, Cancellation concepts, Pagination, Search.
Fetch
REACT API INTEGRATION: Fetch. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fetch.
- Apply Fetch in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Axios awareness
REACT API INTEGRATION: Axios awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Axios awareness.
- Apply Axios awareness 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.
Retries
REACT API INTEGRATION: 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.
Cancellation concepts
REACT API INTEGRATION: Cancellation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cancellation concepts.
- Apply Cancellation concepts 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.
Search
REACT API INTEGRATION: 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.
7 curriculum topics: Rendering, Unnecessary rerenders, Memoization, Lazy loading, Code splitting, Bundle size, Virtualization concepts.
Rendering
REACT PERFORMANCE: Rendering. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rendering.
- Apply Rendering in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unnecessary rerenders
REACT PERFORMANCE: Unnecessary rerenders. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unnecessary rerenders.
- Apply Unnecessary rerenders 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 size
REACT PERFORMANCE: Bundle size. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Bundle size.
- Apply Bundle size in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Virtualization concepts
REACT PERFORMANCE: Virtualization concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Virtualization concepts.
- Apply Virtualization concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Semantics, Labels, Keyboard navigation, Focus, Accessible forms, ARIA awareness.
Semantics
REACT ACCESSIBILITY: Semantics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Semantics.
- Apply Semantics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Labels
REACT 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
REACT 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.
Focus
REACT ACCESSIBILITY: Focus. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Focus.
- Apply Focus in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Accessible forms
REACT 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.
ARIA awareness
REACT ACCESSIBILITY: ARIA awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ARIA awareness.
- Apply ARIA awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
15 curriculum topics: XSS, Unsafe HTML, Authentication UI, Token-storage risks, Secure cookies, Dependency security, Home, Product listing and 7 more topics.
XSS
REACT 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.
Unsafe HTML
REACT SECURITY: Unsafe HTML. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unsafe HTML.
- Apply Unsafe HTML in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication UI
REACT SECURITY: Authentication UI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication UI.
- Apply Authentication UI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token-storage risks
REACT 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
REACT 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.
Dependency security
REACT 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.
Home
REACT SECURITY: Home. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Home.
- Apply Home in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Product listing
REACT SECURITY: Product listing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Product listing.
- Apply Product listing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Search
REACT SECURITY: 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.
Filter
REACT SECURITY: Filter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filter.
- Apply Filter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Product detail
REACT SECURITY: Product detail. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Product detail.
- Apply Product detail in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cart
REACT SECURITY: 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.
Login
REACT SECURITY: 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.
Profile
REACT SECURITY: Profile. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Profile.
- Apply Profile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Responsive UI
REACT SECURITY: Responsive UI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Responsive UI.
- Apply Responsive UI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Node runtime, V8, Modules, Npm, Package.json, Environment variables.
Node runtime
NODE.JS FUNDAMENTALS: Node runtime. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Node runtime.
- Apply Node runtime in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
V8
NODE.JS FUNDAMENTALS: V8. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of V8.
- Apply V8 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules
NODE.JS FUNDAMENTALS: 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.
Npm
NODE.JS FUNDAMENTALS: Npm. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Npm.
- Apply Npm in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Package.json
NODE.JS FUNDAMENTALS: Package.json. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Package.json.
- Apply Package.json in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment variables
NODE.JS FUNDAMENTALS: 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.
4 curriculum topics: ECMAScript modules, CommonJS awareness, Import/export, Module resolution.
ECMAScript modules
NODE MODULE SYSTEM: ECMAScript modules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ECMAScript modules.
- Apply ECMAScript modules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CommonJS awareness
NODE MODULE SYSTEM: CommonJS awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CommonJS awareness.
- Apply CommonJS awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Import/export
NODE MODULE SYSTEM: Import/export. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Import/export.
- Apply Import/export in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Module resolution
NODE MODULE SYSTEM: Module resolution. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Module resolution.
- Apply Module resolution in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Event loop, Asynchronous I/O, Timers, Promises, Blocking vs non-blocking.
Event loop
NODE EVENT LOOP: Event loop. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Event loop.
- Apply Event loop in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Asynchronous I/O
NODE EVENT LOOP: Asynchronous I/O. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Asynchronous I/O.
- Apply Asynchronous I/O in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Timers
NODE EVENT LOOP: Timers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Timers.
- Apply Timers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Promises
NODE EVENT LOOP: 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.
Blocking vs non-blocking
NODE EVENT LOOP: Blocking vs non-blocking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blocking vs non-blocking.
- Apply Blocking vs non-blocking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Fs, Paths, Streams, Buffers, File processing.
Fs
NODE FILE SYSTEM: Fs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fs.
- Apply Fs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Paths
NODE FILE SYSTEM: Paths. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Paths.
- Apply Paths in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streams
NODE FILE SYSTEM: Streams. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streams.
- Apply Streams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Buffers
NODE FILE SYSTEM: Buffers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Buffers.
- Apply Buffers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File processing
NODE FILE SYSTEM: File processing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File processing.
- Apply File processing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Readable, Writable, Transform, Backpressure.
Readable
NODE STREAMS: Readable. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Readable.
- Apply Readable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Writable
NODE STREAMS: Writable. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Writable.
- Apply Writable in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Transform
NODE STREAMS: Transform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Transform.
- Apply Transform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backpressure
NODE STREAMS: Backpressure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Backpressure.
- Apply Backpressure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Application, Routers, Routes, Middleware, Error middleware.
Application
EXPRESS 5: Application. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Application.
- Apply Application in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routers
EXPRESS 5: Routers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Routers.
- Apply Routers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Routes
EXPRESS 5: 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.
Middleware
EXPRESS 5: Middleware. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Middleware.
- Apply Middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error middleware
EXPRESS 5: Error middleware. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error middleware.
- Apply Error middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Express Middleware.
Express Middleware
Understand:; Request; Logging; Authentication; Validation; Controller; Response
- Explain the core concepts and architecture of Express Middleware.
- Apply Express Middleware in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Architecture.
Api Architecture
Recommended structure:; text; src/; ├── modules/; │ ├── users/; │ ├── products/; │ └── orders/; ├── middleware/; ├── config/; ├── database/; ├── shared/; └── app.ts
- Explain the core concepts and architecture of Api Architecture.
- Apply Api Architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: Resource modeling, Status codes, Validation, Pagination, Filtering, Sorting, Search, Versioning and 2 more topics.
Resource modeling
REST API ENGINEERING: 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.
Status codes
REST API ENGINEERING: 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
REST API ENGINEERING: Validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Validation.
- Apply Validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
REST API ENGINEERING: 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
REST API ENGINEERING: 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.
Sorting
REST API ENGINEERING: 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.
Search
REST API ENGINEERING: 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
REST API ENGINEERING: 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.
Errors
REST API ENGINEERING: 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.
Idempotency
REST API ENGINEERING: 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.
1 curriculum topics: Api Error Design.
Api Error Design
Example:; json; {; "code": "ORDER_NOT_FOUND",; "message": "Order was not found",; "traceId": "abc-123"; }; Do not expose stack traces publicly.
- Explain the core concepts and architecture of Api Error Design.
- Apply Api Error Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Body, Params, Query, Headers, Zod concepts, Joi concepts.
Body
VALIDATION: Body. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Body.
- Apply Body in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Params
VALIDATION: Params. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Params.
- Apply Params in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Query
VALIDATION: Query. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query.
- Apply Query in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Headers
VALIDATION: Headers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Headers.
- Apply Headers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Zod concepts
VALIDATION: Zod concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Zod concepts.
- Apply Zod concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Joi concepts
VALIDATION: Joi concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Joi concepts.
- Apply Joi concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Databases, Collections, Documents, BSON, ObjectId, CRUD.
Databases
MONGODB FUNDAMENTALS: Databases. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Databases.
- Apply Databases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Collections
MONGODB FUNDAMENTALS: Collections. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Collections.
- Apply Collections in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Documents
MONGODB FUNDAMENTALS: 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.
BSON
MONGODB FUNDAMENTALS: BSON. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of BSON.
- Apply BSON in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
ObjectId
MONGODB FUNDAMENTALS: ObjectId. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ObjectId.
- Apply ObjectId in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CRUD
MONGODB FUNDAMENTALS: CRUD. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CRUD.
- Apply CRUD in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Embed, Reference, How is data accessed?, How often does it change?, How large can it grow?, Does it require independent lifecycle?.
Embed
DOCUMENT DATA MODELING: Embed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Embed.
- Apply Embed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Reference
DOCUMENT DATA MODELING: Reference. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Reference.
- Apply Reference in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
How is data accessed?
DOCUMENT DATA MODELING: How is data accessed?. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of How is data accessed?.
- Apply How is data accessed? in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
How often does it change?
DOCUMENT DATA MODELING: How often does it change?. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of How often does it change?.
- Apply How often does it change? in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
How large can it grow?
DOCUMENT DATA MODELING: How large can it grow?. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of How large can it grow?.
- Apply How large can it grow? in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Does it require independent lifecycle?
DOCUMENT DATA MODELING: Does it require independent lifecycle?. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Does it require independent lifecycle?.
- Apply Does it require independent lifecycle? in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Schema, Model, Validation, Middleware/hooks, Methods, References.
Schema
MONGOOSE: Schema. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Schema.
- Apply Schema in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Model
MONGOOSE: Model. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Model.
- Apply Model in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
MONGOOSE: 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.
Middleware/hooks
MONGOOSE: Middleware/hooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Middleware/hooks.
- Apply Middleware/hooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Methods
MONGOOSE: Methods. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Methods.
- Apply Methods in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
References
MONGOOSE: References. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of References.
- Apply References in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Single-field indexes, Compound indexes, Unique indexes, Text/search awareness, TTL indexes.
Single-field indexes
MONGODB INDEXES: Single-field indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Single-field indexes.
- Apply Single-field indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Compound indexes
MONGODB INDEXES: Compound indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Compound indexes.
- Apply Compound indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unique indexes
MONGODB INDEXES: Unique indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unique indexes.
- Apply Unique indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Text/search awareness
MONGODB INDEXES: Text/search awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Text/search awareness.
- Apply Text/search awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
TTL indexes
MONGODB INDEXES: TTL indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of TTL indexes.
- Apply TTL indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Query patterns, Indexes, Projection, Pagination, Explain-plan concepts.
Query patterns
QUERY OPTIMIZATION: Query patterns. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Query patterns.
- Apply Query patterns in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Indexes
QUERY OPTIMIZATION: 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.
Projection
QUERY OPTIMIZATION: Projection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Projection.
- Apply Projection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Pagination
QUERY OPTIMIZATION: 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.
Explain-plan concepts
QUERY OPTIMIZATION: Explain-plan concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Explain-plan concepts.
- Apply Explain-plan concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
11 curriculum topics: $match, $project, $group, $sort, $lookup, $unwind, $facet, Monthly revenue and 3 more topics.
$match
AGGREGATION PIPELINE: $match. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $match.
- Apply $match in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
$project
AGGREGATION PIPELINE: $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.
$group
AGGREGATION PIPELINE: $group. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $group.
- Apply $group in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
$sort
AGGREGATION PIPELINE: $sort. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $sort.
- Apply $sort in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
$lookup
AGGREGATION PIPELINE: $lookup. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $lookup.
- Apply $lookup in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
$unwind
AGGREGATION PIPELINE: $unwind. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $unwind.
- Apply $unwind in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
$facet
AGGREGATION PIPELINE: $facet. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of $facet.
- Apply $facet in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Monthly revenue
AGGREGATION PIPELINE: Monthly revenue. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Monthly revenue.
- Apply Monthly revenue in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Top products
AGGREGATION PIPELINE: Top products. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Top products.
- Apply Top products in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Repeat customers
AGGREGATION PIPELINE: Repeat customers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Repeat customers.
- Apply Repeat customers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Category performance
AGGREGATION PIPELINE: Category performance. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Category performance.
- Apply Category performance in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Mongodb Transactions.
Mongodb Transactions
Teach when multi-document transactions are required and when better document modeling avoids unnecessary transactions.
- Explain the core concepts and architecture of Mongodb Transactions.
- Apply Mongodb Transactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Replication, Replica sets, Sharding, Shard keys, Availability.
Replication
MONGODB SCALABILITY: Replication. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Replication.
- Apply Replication in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Replica sets
MONGODB SCALABILITY: Replica sets. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Replica sets.
- Apply Replica sets in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sharding
MONGODB SCALABILITY: Sharding. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sharding.
- Apply Sharding in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Shard keys
MONGODB SCALABILITY: Shard keys. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Shard keys.
- Apply Shard keys in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Availability
MONGODB SCALABILITY: Availability. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Availability.
- Apply Availability in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Managed clusters, Security, Connection configuration, Backup concepts, Monitoring, Network access.
Managed clusters
MONGODB ATLAS: Managed clusters. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Managed clusters.
- Apply Managed clusters in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Security
MONGODB ATLAS: 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.
Connection configuration
MONGODB ATLAS: Connection configuration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Connection configuration.
- Apply Connection configuration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Backup concepts
MONGODB ATLAS: Backup concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Backup concepts.
- Apply Backup concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Monitoring
MONGODB ATLAS: Monitoring. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Monitoring.
- Apply Monitoring in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Network access
MONGODB ATLAS: Network access. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Network access.
- Apply Network access in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Session-Based, Token-Based, JWT, OAuth2/OIDC concepts.
Session-Based
AUTHENTICATION: Session-Based. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Session-Based.
- Apply Session-Based in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token-Based
AUTHENTICATION: Token-Based. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token-Based.
- Apply Token-Based 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/OIDC concepts
AUTHENTICATION: OAuth2/OIDC concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of OAuth2/OIDC concepts.
- Apply OAuth2/OIDC concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Password hashing, Salt concepts, Secure password reset, Account enumeration risks.
Password hashing
PASSWORD 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.
Salt concepts
PASSWORD SECURITY: Salt concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Salt concepts.
- Apply Salt concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secure password reset
PASSWORD SECURITY: Secure password reset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secure password reset.
- Apply Secure password reset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Account enumeration risks
PASSWORD SECURITY: Account enumeration risks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Account enumeration risks.
- Apply Account enumeration risks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Access token, Refresh token, Claims, Expiration, Validation, Rotation, 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.
Claims
JWT: Claims. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Claims.
- Apply Claims in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expiration
JWT: Expiration. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Expiration.
- Apply Expiration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
JWT: 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.
Rotation
JWT: Rotation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rotation.
- Apply Rotation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Revocation concepts
JWT: Revocation concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Revocation concepts.
- Apply Revocation concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Rbac.
Rbac
Roles:; text; CUSTOMER; SUPPORT; MANAGER; ADMIN; Backend enforces access.
- Explain the core concepts and architecture of Rbac.
- Apply Rbac in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Object-Level Authorization.
Object-Level Authorization
Scenario:; User 10 requests:; GET /users/25/orders; Authentication is valid.; But ownership fails.; Return:; 403 Forbidden
- Explain the core concepts and architecture of Object-Level Authorization.
- Apply Object-Level Authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: External identity, Authorization code, PKCE, Scopes, Social login concepts.
External identity
OAUTH2 / OIDC: External identity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of External identity.
- Apply External identity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
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.
Social login concepts
OAUTH2 / OIDC: Social login concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Social login concepts.
- Apply Social login concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
17 curriculum topics: XSS, CSRF, NoSQL injection, Broken authorization, Authentication attacks, CORS, Rate limiting, Secret exposure and 9 more topics.
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.
NoSQL injection
WEB SECURITY: NoSQL injection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of NoSQL injection.
- Apply NoSQL injection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Broken authorization
WEB SECURITY: Broken authorization. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Broken authorization.
- Apply Broken authorization in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Authentication attacks
WEB SECURITY: Authentication attacks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Authentication attacks.
- Apply Authentication attacks 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.
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.
Secret exposure
WEB SECURITY: Secret exposure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secret exposure.
- Apply Secret exposure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency risks
WEB SECURITY: Dependency risks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency risks.
- Apply Dependency risks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Malicious file uploads
WEB SECURITY: Malicious file uploads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Malicious file uploads.
- Apply Malicious file uploads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Registration
WEB SECURITY: 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.
Email verification
WEB SECURITY: Email verification. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Email verification.
- Apply Email verification in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Login
WEB SECURITY: 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.
Refresh tokens
WEB SECURITY: Refresh tokens. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Refresh tokens.
- Apply Refresh tokens in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Password reset
WEB SECURITY: Password reset. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Password reset.
- Apply Password reset in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RBAC
WEB SECURITY: 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.
Audit history
WEB SECURITY: Audit history. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Audit history.
- Apply Audit history in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Key/value, TTL, Caching, Session concepts, Rate limiting, Temporary state.
Key/value
REDIS: Key/value. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Key/value.
- Apply Key/value 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.
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.
Session concepts
REDIS: Session concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Session concepts.
- Apply Session concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limiting
REDIS: Rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limiting.
- Apply Rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Temporary state
REDIS: Temporary state. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Temporary state.
- Apply Temporary state in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Cache-Aside.
Cache-Aside
Flow:; Request; Check Redis; Hit → Return; or; Miss; MongoDB; Cache; Return
- Explain the core concepts and architecture of Cache-Aside.
- Apply Cache-Aside in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Without Cache, Cache Hit.
Without Cache
CACHE INVALIDATION: Without Cache. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Without Cache.
- Apply Without Cache in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache Hit
CACHE INVALIDATION: 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.
6 curriculum topics: Email, PDF reports, Imports, Exports, Image processing, Notifications.
BACKGROUND JOBS: Email. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Email.
- Apply Email in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
PDF reports
BACKGROUND JOBS: PDF reports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of PDF reports.
- Apply PDF reports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Imports
BACKGROUND JOBS: 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.
Exports
BACKGROUND JOBS: Exports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exports.
- Apply Exports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Image processing
BACKGROUND JOBS: Image processing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Image processing.
- Apply Image processing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notifications
BACKGROUND JOBS: 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.
6 curriculum topics: BullMQ concepts, Redis-backed jobs, Queue, Worker, Retry, Scheduling.
BullMQ concepts
JOB QUEUES: BullMQ concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of BullMQ concepts.
- Apply BullMQ concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis-backed jobs
JOB QUEUES: Redis-backed jobs. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redis-backed jobs.
- Apply Redis-backed jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue
JOB QUEUES: 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.
Worker
JOB QUEUES: Worker. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Worker.
- Apply Worker in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
JOB QUEUES: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Scheduling
JOB QUEUES: Scheduling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Scheduling.
- Apply Scheduling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Idempotent Jobs.
Idempotent Jobs
Jobs may run more than once.; Design business operations accordingly.
- Explain the core concepts and architecture of Idempotent Jobs.
- Apply Idempotent Jobs in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Signature verification, Replay protection, Retry, Duplicate webhook delivery, Idempotency.
Signature verification
WEBHOOKS: Signature verification. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Signature verification.
- Apply Signature verification in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Replay protection
WEBHOOKS: Replay protection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Replay protection.
- Apply Replay protection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
WEBHOOKS: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Duplicate webhook delivery
WEBHOOKS: Duplicate webhook delivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Duplicate webhook delivery.
- Apply Duplicate webhook delivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
WEBHOOKS: Idempotency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Idempotency.
- Apply Idempotency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Multipart uploads, File validation, MIME validation, Maximum size, Malware-scanning concepts, Storage separation.
Multipart uploads
FILE UPLOADS: Multipart uploads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Multipart uploads.
- Apply Multipart uploads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
MIME validation
FILE UPLOADS: MIME validation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of MIME validation.
- Apply MIME validation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Maximum size
FILE UPLOADS: Maximum size. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Maximum size.
- Apply Maximum size in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Malware-scanning concepts
FILE UPLOADS: Malware-scanning concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Malware-scanning concepts.
- Apply Malware-scanning concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Storage separation
FILE UPLOADS: Storage separation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Storage separation.
- Apply Storage separation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Profile images, Documents, Exports, Media.
Profile images
AWS S3: 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: 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: 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.
Media
AWS S3: Media. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Media.
- Apply Media in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Live chat, Notifications, Online status.
Live chat
WEBSOCKETS: Live chat. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Live chat.
- Apply Live 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.
Online status
WEBSOCKETS: Online status. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Online status.
- Apply Online status in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Agents, Customers, Rooms, Messages, Online status, Typing state, Notification.
Agents
SOCKET.IO AWARENESS: Agents. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Agents.
- Apply Agents in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Customers
SOCKET.IO AWARENESS: 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.
Rooms
SOCKET.IO AWARENESS: Rooms. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rooms.
- Apply Rooms in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Messages
SOCKET.IO AWARENESS: Messages. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Messages.
- Apply Messages in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Online status
SOCKET.IO AWARENESS: Online status. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Online status.
- Apply Online status in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Typing state
SOCKET.IO AWARENESS: Typing state. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Typing state.
- Apply Typing state in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notification
SOCKET.IO AWARENESS: Notification. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Notification.
- Apply Notification in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Job progress, AI responses, Feeds.
Job progress
SERVER-SENT EVENTS: Job progress. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Job progress.
- Apply Job progress in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
Feeds
SERVER-SENT EVENTS: Feeds. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Feeds.
- Apply Feeds in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Full Stack Integration.
Full Stack Integration
Architecture:; text; React + TypeScript; REST API; Node.js + Express; MongoDB + Redis
- Explain the core concepts and architecture of Full Stack Integration.
- Apply Full Stack Integration in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Login UI, Protected routes, Session/token refresh, Logout, User state.
Login UI
AUTHENTICATION INTEGRATION: Login UI. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Login UI.
- Apply Login UI in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Protected routes
AUTHENTICATION INTEGRATION: 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.
Session/token refresh
AUTHENTICATION INTEGRATION: Session/token refresh. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Session/token refresh.
- Apply Session/token refresh in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Logout
AUTHENTICATION INTEGRATION: 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.
User state
AUTHENTICATION INTEGRATION: User state. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of User state.
- Apply User state in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Api Cors Design.
Api Cors Design
Teach proper origin policy.; Do not simply use:; text; Access-Control-Allow-Origin: *; for authenticated production applications.
- Explain the core concepts and architecture of Api Cors Design.
- Apply Api Cors Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
2 curriculum topics: Company A, Company B.
Company A
MULTI-TENANT SaaS: Company A. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Company A.
- Apply Company A in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Company B
MULTI-TENANT SaaS: Company B. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Company B.
- Apply Company B in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Unit Testing, Integration Testing, API Testing, Component Testing, End-to-End Testing.
Unit Testing
TESTING FOUNDATION: Unit Testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unit Testing.
- Apply Unit Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Integration Testing
TESTING FOUNDATION: Integration Testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Integration Testing.
- Apply Integration Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API Testing
TESTING FOUNDATION: API Testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API Testing.
- Apply API Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Component Testing
TESTING FOUNDATION: Component Testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Component Testing.
- Apply Component Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
End-to-End Testing
TESTING FOUNDATION: End-to-End Testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of End-to-End Testing.
- Apply End-to-End Testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Services, Utility functions, Domain rules.
Services
BACKEND UNIT TESTING: 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.
Utility functions
BACKEND UNIT TESTING: Utility functions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Utility functions.
- Apply Utility functions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain rules
BACKEND UNIT TESTING: Domain rules. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Domain rules.
- Apply Domain rules in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Status codes, Validation, Auth, RBAC, Errors, DB behavior.
Status codes
API TESTING: Status codes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Status codes.
- Apply Status codes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Validation
API 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.
Auth
API TESTING: Auth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Auth.
- Apply Auth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RBAC
API TESTING: 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.
Errors
API TESTING: Errors. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Errors.
- Apply Errors in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB behavior
API TESTING: DB behavior. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DB behavior.
- Apply DB behavior in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Component tests, Behavior-based testing, User interactions, API mocking concepts.
Component tests
REACT 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.
Behavior-based testing
REACT TESTING: Behavior-based testing. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Behavior-based testing.
- Apply Behavior-based testing in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
User interactions
REACT TESTING: User interactions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of User interactions.
- Apply User interactions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
API mocking concepts
REACT TESTING: API mocking concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API mocking concepts.
- Apply API mocking concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Playwright concepts.
Playwright concepts
E2E 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.
6 curriculum topics: ESLint, Formatting, Type checks, Naming, Code review, Clean architecture.
ESLint
CODE QUALITY: ESLint. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of ESLint.
- Apply ESLint in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Formatting
CODE QUALITY: Formatting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Formatting.
- Apply Formatting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Type checks
CODE QUALITY: Type checks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Type checks.
- Apply Type checks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Naming
CODE QUALITY: 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.
Code review
CODE QUALITY: 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.
Clean architecture
CODE QUALITY: Clean architecture. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Clean architecture.
- Apply Clean architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Blocking event loop, CPU-bound work, Async I/O, Streams, Worker threads concepts.
Blocking event loop
NODE PERFORMANCE: Blocking event loop. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blocking event loop.
- Apply Blocking event loop in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU-bound work
NODE PERFORMANCE: CPU-bound work. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CPU-bound work.
- Apply CPU-bound work in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Async I/O
NODE PERFORMANCE: Async I/O. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Async I/O.
- Apply Async I/O in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streams
NODE PERFORMANCE: Streams. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Streams.
- Apply Streams in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Worker threads concepts
NODE PERFORMANCE: Worker threads concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Worker threads concepts.
- Apply Worker threads concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Blocking code, CPU workload, Worker threads, Background workers, Architectural separation.
Blocking code
EVENT LOOP BLOCKING LAB: Blocking code. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blocking code.
- Apply Blocking code in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
CPU workload
EVENT LOOP BLOCKING LAB: CPU workload. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of CPU workload.
- Apply CPU workload in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Worker threads
EVENT LOOP BLOCKING LAB: Worker threads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Worker threads.
- Apply Worker threads in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Background workers
EVENT LOOP BLOCKING LAB: Background workers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Background workers.
- Apply Background workers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Architectural separation
EVENT LOOP BLOCKING LAB: Architectural separation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Architectural separation.
- Apply Architectural separation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Missing indexes, Large documents, Unbounded queries, Expensive aggregation, Pagination.
Missing indexes
DATABASE PERFORMANCE: Missing indexes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Missing indexes.
- Apply Missing indexes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Large documents
DATABASE PERFORMANCE: Large documents. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Large documents.
- Apply Large documents in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unbounded queries
DATABASE PERFORMANCE: Unbounded queries. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unbounded queries.
- Apply Unbounded queries in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Expensive aggregation
DATABASE PERFORMANCE: Expensive aggregation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Expensive aggregation.
- Apply Expensive aggregation 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.
2 curriculum topics: Offset Pagination, Cursor Pagination.
Offset Pagination
PAGINATION: Offset Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Offset Pagination.
- Apply Offset Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cursor Pagination
PAGINATION: Cursor Pagination. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cursor Pagination.
- Apply Cursor Pagination in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: P50, P95, P99, Throughput, Error rate.
P50
API PERFORMANCE: P50. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P50.
- Apply P50 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P95
API PERFORMANCE: P95. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P95.
- Apply P95 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
P99
API PERFORMANCE: P99. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of P99.
- Apply P99 in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Throughput
API PERFORMANCE: Throughput. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Throughput.
- Apply Throughput in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Error rate
API PERFORMANCE: Error rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Error rate.
- Apply Error rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Fixed window, Sliding window concepts, Token bucket concepts, Redis-backed rate limiting.
Fixed window
RATE LIMITING: Fixed window. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Fixed window.
- Apply Fixed window in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Sliding window concepts
RATE LIMITING: Sliding window concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Sliding window concepts.
- Apply Sliding window concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Token bucket concepts
RATE LIMITING: Token bucket concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Token bucket concepts.
- Apply Token bucket concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Redis-backed rate limiting
RATE LIMITING: Redis-backed rate limiting. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Redis-backed rate limiting.
- Apply Redis-backed rate limiting in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
5 curriculum topics: Modular monolith first, Service boundaries, Independent deployment, Database ownership, Distributed-system complexity.
Modular monolith first
MICROSERVICES FUNDAMENTALS: Modular monolith first. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Modular monolith first.
- Apply Modular monolith first in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
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.
Distributed-system complexity
MICROSERVICES FUNDAMENTALS: Distributed-system complexity. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Distributed-system complexity.
- Apply Distributed-system complexity in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Node Microservices.
Node Microservices
Example:; text; Identity Service; Product Service; Order Service; Notification Service
- Explain the core concepts and architecture of Node Microservices.
- Apply Node Microservices in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: REST, Events, Queues, Webhooks.
REST
SERVICE COMMUNICATION: REST. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of REST.
- Apply REST in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Events
SERVICE COMMUNICATION: Events. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Events.
- Apply Events in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queues
SERVICE COMMUNICATION: Queues. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queues.
- Apply Queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Webhooks
SERVICE COMMUNICATION: Webhooks. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Webhooks.
- Apply Webhooks in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
8 curriculum topics: Kafka, RabbitMQ, AWS SQS, Producer, Consumer, Retries, Dead-letter queues, Idempotency.
Kafka
MESSAGE BROKER AWARENESS: Kafka. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Kafka.
- Apply Kafka in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RabbitMQ
MESSAGE BROKER AWARENESS: RabbitMQ. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of RabbitMQ.
- Apply RabbitMQ in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AWS SQS
MESSAGE BROKER AWARENESS: AWS SQS. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AWS SQS.
- Apply AWS SQS in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Producer
MESSAGE BROKER AWARENESS: 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
MESSAGE BROKER AWARENESS: 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.
Retries
MESSAGE BROKER AWARENESS: 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.
Dead-letter queues
MESSAGE BROKER AWARENESS: Dead-letter queues. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dead-letter queues.
- Apply Dead-letter queues in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Idempotency
MESSAGE BROKER AWARENESS: 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: Timeout, Retry, Exponential backoff, Circuit breaker concepts, Bulkhead concepts.
Timeout
RESILIENCE: Timeout. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Timeout.
- Apply Timeout in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Retry
RESILIENCE: Retry. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Retry.
- Apply Retry in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Exponential backoff
RESILIENCE: Exponential backoff. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Exponential backoff.
- Apply Exponential backoff in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Circuit breaker concepts
RESILIENCE: Circuit breaker concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Circuit breaker concepts.
- Apply Circuit breaker concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Bulkhead concepts
RESILIENCE: Bulkhead concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Bulkhead concepts.
- Apply Bulkhead concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
6 curriculum topics: Controllers, Providers, Modules, Dependency injection, Decorators, Structured Node backend architecture.
Controllers
NESTJS AWARENESS: Controllers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Controllers.
- Apply Controllers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Providers
NESTJS AWARENESS: Providers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Providers.
- Apply Providers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Modules
NESTJS AWARENESS: 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.
Dependency injection
NESTJS AWARENESS: 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.
Decorators
NESTJS AWARENESS: 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.
Structured Node backend architecture
NESTJS AWARENESS: Structured Node backend architecture. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Structured Node backend architecture.
- Apply Structured Node backend architecture in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Logging.
Logging
Teach structured logs.; Example:; json; {; "traceId": "abc",; "method": "POST",; "path": "/orders",; "durationMs": 81,; "status": 201; }
- Explain the core concepts and architecture of Logging.
- Apply Logging in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
9 curriculum topics: Logs, Metrics, Traces, Request rate, Errors, Latency, DB latency, Cache hits and 1 more topics.
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.
Request rate
OBSERVABILITY: Request rate. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Request rate.
- Apply Request rate in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Errors
OBSERVABILITY: 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
OBSERVABILITY: Latency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Latency.
- Apply Latency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DB latency
OBSERVABILITY: DB latency. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DB latency.
- Apply DB latency in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cache hits
OBSERVABILITY: Cache hits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cache hits.
- Apply Cache hits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Queue depth
OBSERVABILITY: Queue depth. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Queue depth.
- Apply Queue depth in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Trace, Span, Context propagation.
Trace
OPENTELEMETRY: Trace. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Trace.
- Apply Trace in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Span
OPENTELEMETRY: Span. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Span.
- Apply Span in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Context propagation
OPENTELEMETRY: Context propagation. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Context propagation.
- Apply Context propagation in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Release, Stack trace, Environment, Affected user/session correlation without oversharing sensitive data.
Release
ERROR MONITORING: Release. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Release.
- Apply Release in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Stack trace
ERROR MONITORING: Stack trace. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Stack trace.
- Apply Stack trace in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment
ERROR MONITORING: Environment. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Environment.
- Apply Environment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Affected user/session correlation without oversharing sensitive data
ERROR MONITORING: Affected user/session correlation without oversharing sensitive data. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Affected user/session correlation without oversharing sensitive data.
- Apply Affected user/session correlation without oversharing sensitive data 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, Networking, Volumes, Environment variables.
Images
DOCKER: Images. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Images.
- Apply Images in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Containers
DOCKER: Containers. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Containers.
- Apply Containers in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dockerfile
DOCKER: Dockerfile. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dockerfile.
- Apply Dockerfile in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Multi-stage 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.
Networking
DOCKER: Networking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Networking.
- Apply Networking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Volumes
DOCKER: Volumes. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Volumes.
- Apply Volumes in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Environment variables
DOCKER: Environment variables. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Environment variables.
- Apply Environment variables in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Docker Compose.
Docker Compose
Local stack:; text; React; Node API; MongoDB; Redis; Worker
- 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.
7 curriculum topics: Filesystem, Permissions, Processes, Logs, Environment variables, Ports, Network commands concepts.
Filesystem
LINUX FUNDAMENTALS: Filesystem. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Filesystem.
- Apply Filesystem in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Permissions
LINUX FUNDAMENTALS: Permissions. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Permissions.
- Apply Permissions in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Processes
LINUX FUNDAMENTALS: 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.
Logs
LINUX FUNDAMENTALS: 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.
Environment variables
LINUX FUNDAMENTALS: 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.
Ports
LINUX FUNDAMENTALS: Ports. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Ports.
- Apply Ports in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Network commands concepts
LINUX FUNDAMENTALS: Network commands concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Network commands concepts.
- Apply Network commands concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: IAM, EC2, S3, CloudWatch, Networking, Load balancer, DNS concepts.
IAM
AWS: 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: 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: 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.
CloudWatch
AWS: 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.
Networking
AWS: 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.
Load balancer
AWS: Load balancer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Load balancer.
- Apply Load balancer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
DNS concepts
AWS: DNS concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of DNS concepts.
- Apply DNS concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Mongodb Atlas + Aws.
Mongodb Atlas + Aws
Teach secure connectivity and production configuration concepts.
- Explain the core concepts and architecture of Mongodb Atlas + Aws.
- Apply Mongodb Atlas + Aws in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Aws Deployment.
Aws Deployment
Architecture:; React; CDN/static hosting concepts; Node APIs; MongoDB; Redis
- Explain the core concepts and architecture of Aws Deployment.
- Apply Aws Deployment in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
3 curriculum topics: Lambda, API Gateway, Event-driven workloads.
Lambda
SERVERLESS AWARENESS: 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.
API Gateway
SERVERLESS AWARENESS: API Gateway. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API Gateway.
- Apply API Gateway in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Event-driven workloads
SERVERLESS AWARENESS: Event-driven workloads. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Event-driven workloads.
- Apply Event-driven workloads 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; Type Check; Unit Tests; Integration Tests; Build; Docker Image; Deploy; Health Verification
- 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 production-style CI workflows.
- 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.
3 curriculum topics: Configurations, Secrets, Databases.
Configurations
ENVIRONMENTS: Configurations. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Configurations.
- Apply Configurations in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Secrets
ENVIRONMENTS: 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.
Databases
ENVIRONMENTS: Databases. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Databases.
- Apply Databases in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
4 curriculum topics: Rolling, Blue/green concepts, Canary concepts, Rollback.
Rolling
DEPLOYMENT STRATEGIES: Rolling. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rolling.
- Apply Rolling in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Blue/green concepts
DEPLOYMENT STRATEGIES: Blue/green concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Blue/green concepts.
- Apply Blue/green concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Canary concepts
DEPLOYMENT STRATEGIES: Canary concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Canary concepts.
- Apply Canary concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rollback
DEPLOYMENT STRATEGIES: Rollback. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rollback.
- Apply Rollback 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.
4 curriculum topics: API, Application Services, Domain, Database/Infrastructure.
API
CLEAN ARCHITECTURE: API. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of API.
- Apply API in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Application Services
CLEAN ARCHITECTURE: Application Services. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Application Services.
- Apply Application Services in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Domain
CLEAN ARCHITECTURE: Domain. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Domain.
- Apply Domain in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Database/Infrastructure
CLEAN ARCHITECTURE: Database/Infrastructure. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Database/Infrastructure.
- Apply Database/Infrastructure in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: Repository, Service, Factory, Strategy, Adapter, Observer, Dependency Injection concepts.
Repository
DESIGN PATTERNS: Repository. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Repository.
- Apply Repository in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Service
DESIGN PATTERNS: Service. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Service.
- Apply Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Factory
DESIGN PATTERNS: Factory. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Factory.
- Apply Factory in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Strategy
DESIGN PATTERNS: Strategy. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Strategy.
- Apply Strategy in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Adapter
DESIGN PATTERNS: Adapter. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Adapter.
- Apply Adapter in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Observer
DESIGN PATTERNS: Observer. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Observer.
- Apply Observer in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Dependency Injection concepts
DESIGN PATTERNS: Dependency Injection concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Dependency Injection concepts.
- Apply Dependency Injection concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
1 curriculum topics: Low-Level Design.
Low-Level Design
Problems:; 1. Shopping Cart; 2. Notification Service; 3. Parking Lot; 4. Booking System; 5. Task Manager; 6. Payment Service; 7. Rate Limiter
- Explain the core concepts and architecture of Low-Level Design.
- Apply Low-Level Design in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
10 curriculum topics: URL Shortener, E-Commerce Platform, Chat System, Food Delivery, Course Platform, Ticket Booking, Notification Service, File Upload Service and 2 more topics.
URL Shortener
SYSTEM DESIGN: URL Shortener. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of URL Shortener.
- Apply URL Shortener in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
E-Commerce Platform
SYSTEM DESIGN: E-Commerce Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of E-Commerce Platform.
- Apply E-Commerce Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Chat System
SYSTEM DESIGN: Chat System. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Chat System.
- Apply Chat System in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Food Delivery
SYSTEM DESIGN: Food Delivery. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Food Delivery.
- Apply Food Delivery in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Course Platform
SYSTEM DESIGN: Course Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Course Platform.
- Apply Course Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Ticket Booking
SYSTEM DESIGN: Ticket Booking. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Ticket Booking.
- Apply Ticket Booking in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Notification Service
SYSTEM DESIGN: Notification Service. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Notification Service.
- Apply Notification Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
File Upload Service
SYSTEM DESIGN: File Upload Service. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of File Upload Service.
- Apply File Upload Service in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Social Feed
SYSTEM DESIGN: Social Feed. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Social Feed.
- Apply Social Feed in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
SaaS Platform
SYSTEM DESIGN: SaaS Platform. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of SaaS Platform.
- Apply SaaS Platform in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
7 curriculum topics: LLM API basics, Streaming, Structured responses, AI chat interface, Tool-call concepts, Embeddings awareness, RAG fundamentals.
LLM API basics
GENAI IN MERN: LLM API basics. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of LLM API basics.
- Apply LLM API basics in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Streaming
GENAI IN MERN: 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 responses
GENAI IN MERN: Structured responses. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Structured responses.
- Apply Structured responses in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
AI chat interface
GENAI IN MERN: AI chat interface. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of AI chat interface.
- Apply AI chat interface in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Tool-call concepts
GENAI IN MERN: Tool-call concepts. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Tool-call concepts.
- Apply Tool-call concepts in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Embeddings awareness
GENAI IN MERN: Embeddings awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Embeddings awareness.
- Apply Embeddings awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
RAG fundamentals
GENAI IN MERN: 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 awareness, Unauthorized document access, Rate limits, Cost controls, Output validation, Secret protection.
Prompt injection awareness
AI SECURITY: Prompt injection awareness. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Prompt injection awareness.
- Apply Prompt injection awareness in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Unauthorized document access
AI SECURITY: Unauthorized document access. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Unauthorized document access.
- Apply Unauthorized document access in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Rate limits
AI SECURITY: Rate limits. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Rate limits.
- Apply Rate limits in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
Cost controls
AI SECURITY: Cost controls. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Cost controls.
- Apply Cost controls 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.
Secret protection
AI SECURITY: Secret protection. Core concepts, implementation patterns, hands-on application, integration trade-offs, security and production considerations.
- Explain the core concepts and architecture of Secret protection.
- Apply Secret protection in a full stack or Generative AI product.
- Evaluate implementation trade-offs, security and production considerations.
26 Hands-On Production Capstones & Microservices
Build, deploy, and showcase real-world enterprise architectures on GitHub to prove your production engineering readiness:
Enterprise E-Commerce Microservices & Event-Driven Streaming Platform
Architected with Spring Boot 3.3, Apache Kafka event streams, Redis distributed caching, React 19 UI, and PostgreSQL. Features distributed ACID transaction sagas, payment webhook handling, dynamic inventory locking, and Dockerized Kubernetes deployment.
High-Throughput Banking & Core Transaction Engine
Concurrent multithreaded financial transaction ledger with ACID compliance, optimistic row locking, idempotent payment endpoints, and audit logging.
Real-Time Logistics & Fleet Tracking Service
Bi-directional live vehicle telemetry dashboard processing 10,000+ geo-coordinate events/sec with live map rendering and ETA calculations.
Multi-Tenant SaaS Subscription & Webhook Gateway
Multi-tenant automated billing engine with webhook signature verification, dynamic token bucket rate-limiting, and tenant data isolation schemas.
Distributed URL Shortener & Analytics System (Bitly Scale)
Low-latency URL redirection engine with distributed ID generation (Snowflake), sub-5ms Redis caching, and real-time click analytics.
Automated Cloud DevOps CI/CD Pipeline on AWS
Production containerization pipeline with automated testing, sonar code quality gates, container image vulnerability scanning, and zero-downtime rolling deploys.
AI-Powered Code Reviewer & Assessment Engine
Automated coding interview evaluator that parses Java AST trees, detects algorithmic time complexity, and simulates 1-on-1 voice technical interview feedback.
MockAttempt Academy vs. Traditional Bootcamps & Self-Study
Transparent side-by-side comparison of daily schedule, duration, curriculum, and placement support:
| Feature & Deliverables | MockAttempt Fast-Track Track | Expensive Bootcamps | Self-Study / YouTube |
|---|---|---|---|
| Live Weekend Schedule | Sat & Sun (4 Hours / Day) | 1 - 1.5 Hours / Day | Self-Paced / Inconsistent |
| Duration to Placement Readiness | 4 Months (16 Weeks Weekend) | 6 - 9 Months | 12+ Months (Uncertain) |
| Candidate Placement Guarantee | Unlimited Drives until Placed (or Full Refund) | Limited to 3-6 Months only | None (Apply blindly) |
| Topic Mock Tests & AI Interviews | Integrated for Every Topic (580+ Rounds) | End of Course Only | None |
| Tuition Fee | ₹49,999 ₹98,999 | ₹1,20,000 - ₹2,50,000 | Free (No Mentorship/Jobs) |
Institutional Course Assurances & 100% Placement Policy
100% Job Placement Guarantee
Our placement team arranges unlimited corporate interview drives across 1,050+ hiring partners until you receive an official offer letter. If unplaced, 100% of your tuition fee is refunded.
1-on-1 Expert Faculty Mentorship
Every cohort is taught live by seasoned lead architects from Tier-1 product companies with daily live coding and supervised code reviews.
Frequently Asked Questions
Ready to Become a Top 1% MERN Stack Developer in 3 Months?
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