Curriculum
The Blueprint to Success
Our expert-led curriculum will prepare you for the toughest challenges that you may face in your journey to becoming a skilled programmer.
Course Outline for Beginners
| Segment | Module Type |
Module name | Duration (months) |
|---|---|---|---|
| Programming Fundamentals | Core | Programming Fundamentals - Thinking with AI: Logics, Loops & Control Flow | 1 |
| Core | Programming Fundamentals - Code Smarter with AI: Function & Arrays | 1 | |
| Core | Intermediate DSA : AI Assisted Problem Solving | 1 | |
| Agentic AI | Core | AI & Agents: From Talking to AI to Building One | 1 |
| Advanced DSA | Core | Advanced DSA: Foundations:Core Techniques & Optimization | 1 |
| Core | Advanced DSA: Linear & Non-Linear Structures | 1 | |
| Core | Advanced DSA: Backtracking & Advanced Trees | 1 | |
| Core | Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge | 1 | |
| Databases & SQL | Core | Databases & SQL | 1 |
| Backend | Specialisation | Foundations of Object-Oriented Design & Scalable Systems | 1 |
| Specialisation | Design Principles & Patterns for Extensible Systems | 1 | |
| Specialisation | Applied Design & Machine Coding | 1 | |
| Specialisation | AI-First Backend Capstone Project primer | 1 | |
| Elective | AI-First Backend Capstone Project Advance | 1.5 | |
| Elective | Build a Production-Ready AI-Enabled System | 1 | |
| Fullstack | Specialisation | Web Platform Foundations & UI Systems | 0.5 |
| Specialisation | JavaScript Runtime Systems, Browser APIs & Product Engineering Labs | 1.5 | |
| Specialisation | React and Frontend Product Architecture Fundamentals | 1 | |
| Specialisation | Backend Product Systems, APIs and Production Engineering | 1 | |
| Elective | Backend Product Systems - Deep Dive | 0.5 | |
| Elective | Foundations of AI-Assisted Full-Stack Development | 0.5 | |
| Elective | JavaScript Object System & Engineering Patterns | 0.5 | |
| Elective | React and Frontend Product Architecture Fundamentals Deep Dive | 1 | |
| FDE | Specialisation | Foundations of the Forward Deployed Engineer Role & Production Python | 7.5 |
| Specialisation | Backend Systems, Observability & Advanced Data Engineering | ||
| Specialisation | AI-First Frontends with TypeScript & React | ||
| Specialisation | Cloud, DevOps & Kubernetes for Production Delivery | ||
| Specialisation | LLM Engineering & Customer Consulting (RAG, Prompting & Guardrails) | ||
| Specialisation | Agentic Systems & Enterprise Integrations (Agents, MCP & HITL) | ||
| Specialisation | Secure, Multi-Tenant Application Delivery & Incident Response | ||
| Specialisation | FDE Capstone: End-to-End Customer Engagement (Discovery to Demo Day) | ||
| Elective | Containerization and Orchestration | 1.5 | |
| Elective | AWS : multi-region cloud deep dive- 1.5 months | 1.5 | |
| Elective | Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance - 1 month | 1 | |
| System Design | Elective | Distributed System Design & AI-Integrated Architectures | 1.5 |
| Interview Preparation | Mastering LastMile - Interview Simulation | 1.5 weeks | |
| Data Engineering | Data Engineering | 2 | |
| Advanced DSA | DSA Edge: Advanced Patterns & Interview Techniques | 1 | |
| Product Management for Engineers | 1 | ||
| Gen AI for Software Engineers | 1.5 |
* This module is customised at learner level i.e. a learner can opt for this module at any point during the course post the completion of Data Structures & Algorithms module, once they have demonstrated their command on the concepts of Data Structures & Algorithms module.
** Only 1 Specialisation is allowed per learner. Recorded lectures for the other can be availed via Student Dashboard. At Least 1 Specialisation is mandatory for successful completion of the course.
*** A learner can do as many electives as they want, but only after completion of Core Curriculum.
Course Outline for Intermediate
| Segment | Module Type |
Module name | Duration (months) |
|---|---|---|---|
| Programming Fundamentals | Core | Intermediate DSA : AI Assisted Problem Solving | 1 |
| Agentic AI | Core | AI & Agents: From Talking to AI to Building One | 1 |
| Advanced DSA | Core | Advanced DSA: Foundations:Core Techniques & Optimization | 1 |
| Core | Advanced DSA: Linear & Non-Linear Structures | 1 | |
| Core | Advanced DSA: Backtracking & Advanced Trees | 1 | |
| Core | Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge | 1 | |
| Databases & SQL | Core | Databases & SQL | 1 |
| Backend | Specialisation | Foundations of Object-Oriented Design & Scalable Systems | 1 |
| Specialisation | Design Principles & Patterns for Extensible Systems | 1 | |
| Specialisation | Applied Design & Machine Coding | 1 | |
| Specialisation | AI-First Backend Capstone Project primer | 1 | |
| Specialisation | AI-First Backend Capstone Project Advance | 1.5 | |
| Elective | Build a Production-Ready AI-Enabled System | 1 | |
| Fullstack | Specialisation | Web Platform Foundations & UI Systems | 0.5 |
| Specialisation | JavaScript Runtime Systems, Browser APIs | 1.5 | |
| Specialisation | React and Frontend Product Architecture Fundamentals fundamentals | 1 | |
| Specialisation | Backend Product Systems, APIs and Production Engineering | 1 | |
| Specialisation | Backend Product Systems, Deep Dive | 0.5 | |
| Elective | Foundations of AI-Assisted Full-Stack Development | 0.5 | |
| Elective | Frontend Systems & Machine Coding Mastery | 0.5 | |
| Elective | React and Frontend Product Architecture Fundamentals Deep Dive | 1 | |
| FDE | Specialisation | Foundations of the Forward Deployed Engineer Role & Production Python | 7.5 |
| Specialisation | Backend Systems, Observability & Advanced Data Engineering | ||
| Specialisation | AI-First Frontends with TypeScript & React | ||
| Specialisation | Cloud, DevOps & Kubernetes for Production Delivery | ||
| Specialisation | LLM Engineering & Customer Consulting (RAG, Prompting & Guardrails) | ||
| Specialisation | Agentic Systems & Enterprise Integrations (Agents, MCP & HITL) | ||
| Specialisation | Secure, Multi-Tenant Application Delivery & Incident Response | ||
| Specialisation | FDE Capstone: End-to-End Customer Engagement (Discovery to Demo Day) | ||
| Elective | Containerization and Orchestration | 1.5 | |
| Elective | AWS : multi-region cloud deep dive- 1.5 months | 1.5 | |
| Elective | Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance - 1 month | 1 | |
| System Design | Elective | Distributed System Design & AI-Integrated Architectures | 1.5 |
| Interview Preparation | Mastering LastMile - Interview Simulation | 1.5 weeks | |
| Data Engineering | Data Engineering | 2 | |
| Advanced DSA | DSA Edge: Advanced Patterns & Interview Techniques | 1 | |
| Product Management for Engineers | 1 | ||
| Gen AI for Software Engineers | 1.5 |
* This module is customised at learner level i.e. a learner can opt for this module at any point during the course post the completion of Data Structures & Algorithms module, once they have demonstrated their command on the concepts of Data Structures & Algorithms module.
** Only 1 Specialisation is allowed per learner. Recorded lectures for the other can be availed via Student Dashboard. At Least 1 Specialisation is mandatory for successful completion of the course.
*** A learner can do as many electives as they want, but only after completion of Core Curriculum.
Course Outline for Advanced
| Segment | Module Type |
Module name | Duration (months) |
|---|---|---|---|
| Agentic AI | Core | AI & Agents: From Talking to AI to Building One | 1 |
| Advanced DSA | Core | Advanced DSA: Foundations:Core Techniques & Optimization | 1 |
| Core | Advanced DSA: Linear & Non-Linear Structures | 1 | |
| Core | Advanced DSA: Backtracking & Advanced Trees | 1 | |
| Core | Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge | 1 | |
| Databases & SQL | Core | Databases & SQL | 1 |
| Backend | Specialisation | Foundations of Object-Oriented Design & Scalable Systems | 1 |
| Specialisation | Design Principles & Patterns for Extensible Systems | 1 | |
| Specialisation | Applied Design & Machine Coding | 1 | |
| Specialisation | AI-First Backend Capstone Project primer | 1 | |
| Specialisation | AI-First Backend Capstone Project Advance | 1.5 | |
| Elective | Build a Production-Ready AI-Enabled System | 1 | |
| Fullstack | Specialisation | Web Platform Foundations & UI Systems | 0.5 |
| Specialisation | JavaScript Runtime Systems, Browser APIs | 1.5 | |
| Specialisation | React and Frontend Product Architecture Fundamentals fundamentals | 1 | |
| Specialisation | Backend Product Systems, APIs and Production Engineering | 1 | |
| Specialisation | Backend Product Systems, Deep Dive | 0.5 | |
| Elective | Foundations of AI-Assisted Full-Stack Development | 0.5 | |
| Elective | Frontend Systems & Machine Coding Mastery | 0.5 | |
| Elective | React and Frontend Product Architecture Fundamentals Deep Dive | 1 | |
| FDE | Specialisation | Foundations of the Forward Deployed Engineer Role & Production Python | 7.5 |
| Specialisation | Backend Systems, Observability & Advanced Data Engineering | ||
| Specialisation | AI-First Frontends with TypeScript & React | ||
| Specialisation | Cloud, DevOps & Kubernetes for Production Delivery | ||
| Specialisation | LLM Engineering & Customer Consulting (RAG, Prompting & Guardrails) | ||
| Specialisation | Agentic Systems & Enterprise Integrations (Agents, MCP & HITL) | ||
| Specialisation | Secure, Multi-Tenant Application Delivery & Incident Response | ||
| Specialisation | FDE Capstone: End-to-End Customer Engagement (Discovery to Demo Day) | ||
| Elective | Containerization and Orchestration | 1.5 | |
| Elective | AWS : multi-region cloud deep dive- 1.5 months | 1.5 | |
| Elective | Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance - 1 month | 1 | |
| System Design | core | Distributed System Design & AI-Integrated Architectures | 1.5 |
| Interview Preparation | Elective | Mastering LastMile - Interview Simulation | 1.5 weeks |
| Data Engineering | Data Engineering | 2 | |
| Advanced DSA | DSA Edge: Advanced Patterns & Interview Techniques | 1 | |
| Product Management for Engineers | 1 | ||
| Gen AI for Software Engineers | 1.5 |
* This module is customised at learner level i.e. a learner can opt for this module at any point during the course post the completion of Data Structures & Algorithms module, once they have demonstrated their command on the concepts of Data Structures & Algorithms module.
** Only 1 Specialisation is allowed per learner. Recorded lectures for the other can be availed via Student Dashboard. At Least 1 Specialisation is mandatory for successful completion of the course.
*** A learner can do as many electives as they want, but only after completion of Core Curriculum.
Curriculum
Deep dive
Curriculum Deep Dive for Beginners
Programming Fundamentals
Programming Fundamentals - Thinking with AI: Logics, Loops & Control Flow
- Programming Foundations & AI Awareness
- Operators & Expression Evaluation using AI
- Data Types 1
- Data Types 2 + Reading Inputs
- Operators
- If-Else & AI Edge Case Thinking
- Lab Session on If-Else
- Loops & Iteration Analysis by AI
- Lab Session on Loop
- More problems on Loops & Patterns
- Lab Session on Patterns
- Dual Camera Proctoring
- Data Types, If-Else & Loops & Contest discussion
Programming Fundamentals - Code Smarter with AI: Function & Arrays
- Functions & Modularity: Designing Code with AI
- Lab Session on Functions
- Introduction to Strings
- 1D Array
- Lab Session on 1D Array - 1
- Lab Session on 1D Array - 2
- 2D Array - 1
- Lab Session on 2D Arrays - 1
- Lab Session on 2D Arrays - 2
- Strings in Memory: Visualizing with AI
- Maths Basics & Calculate Iterations
- Revision: Language
- Break
- Contest 2: Functions & Arrays
Intermediate DSA : AI Assisted Problem Solving
- Time Complexity
- Introduction to Arrays & Basics of AI
- Lab Session on TC, SC, Output & Debugging
- Arrays: Prefix Sum & Carry Forward with AI-Assisted Problem Solving
- Lab Session on Prefix Sum & Carry Forward
- Arrays: Arrays techniques & smart prompting
- Lab Session on Memory Management & Sorting Basics
- Bit Manipulations Basics
- Lab Session on 2D Matrices
- Strings & Immutability visualisations through AI
- Lab on Matrix & Strings using AI
- Contest
Agentic AI
AI & Agents: From Talking to AI to Building One
- GenAI World & LLM Landscape
- Prompt Engineering Basics
- Advanced Prompting & AI Safety Basics
- LLM Built-in Power Tools
- RAG
- n8n Automation Workflow
- What Is an AI Agent?
- Building Agents with n8n
- OpenClaw: Personal 24/7 AI Agent
- Multi-Agent Systems
- Debugging AI
Advanced DSA
Advanced DSA: Foundations:Core Techniques & Optimization
- Time Complexity
- Arrays Techniques
- Arrays 1: One Dimensional
- Arrays 2: Two Dimensional
- Lab Session on Arrays
- Bit Manipulation
- Lab Session on Bit Manipulation
- Recursion
- Lab Session on Recursion
- Maths: Modular Arithmetic & GCD
- Hashing
- Lab Session on Hashing
- Sorting 1: Count Sort & Merge Sort
- Sorting 2: Quick Sort & Comparator Problems
- Sample Contest: Dual Camera Proctoring
- Contest 1: Arrays, Bit Manipulation, Recursion, Math, Hashing & Sorting
Advanced DSA: Linear & Non-Linear Structures
- Searching 1: Binary Search on Array
- Searching 2: Binary Search on Answer
- Lab Session on Searching
- Classes, Objects & Linked List Introduction
- Linked List: Basic Problems
- Stacks
- Lab Session on Stacks
- Queues: Implementation & Problems
- Trees 1: Structure & Traversal
- Trees 2: BST
- Lab Session on Binary Trees
- Revision of DSA 1 & 2
- Break
- Contest 2: Searching, Linked List, Stacks, Queues & Trees
Advanced DSA: Backtracking & Advanced Trees
- Maths: Combinatorics Basics & Prime Numbers
- Lab Session on Prime Numbers & 2 Pointers
- Lab Session on Maths & 2 Pointers
- Backtracking
- Lab Session on Backtracking
- Linked List: Sorting and Problems
- Linked List: Doubly Linked List & Detecting Loop
- Trees 4: Morris Inorder Traversal + LCA
- Lab Session on Binary Trees 2
- Hashing 3: Internal Implementation & Problems
- Contest 3: Math, Two Pointers, Backtracking, Linked List & Trees
Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
- Heaps: Introduction
- Heap Sort & Greedy
- Lab Session on Heaps & Greedy
- Lab Session on Interview Problems 1
- DP 1: One Dimensional
- DP 2: Two Dimensional
- DP 3: Knapsack
- Lab Session on Applications of Knapsack
- Graphs 1: Introduction, DFS & Cycle Detection
- Graphs 2: BFS & MST
- Graphs 3: Dijkstra Algo & Topological Sort
- Lab Session on Interview Problems 2
- Revision of DSA 3 & 4
- Contest 4: Heaps, Greedy, DP & Graphs
- Mandatory Skill Evaluation Test: DSA
- Skill Evaluation Test Discussion + How to ace DSA Interview
- DSA : Real World Project 1 (Social Network Analyzer)
- DSA : Real world Project 2 ( Invoice Merger )
Databases & SQL
Databases & SQL
- Introduction to DBMS & Keys
- CRUD Operations - 1
- CRUD Operations - 2
- Joins
- Aggregate Queries
- Joins and Aggregate Queries Working Session
- Subqueries & Views
- Indexing
- Transactions
- Window Functions
- Schema Design - 1
- Schema Design - 2
- Databases & SQL Contest: SQL and Schema Design
Backend
Foundations of Object-Oriented Design & Scalable Systems
- Intro to LLD for Scalable & AI-Ready Systems
- OOP-1: Intro to OOP Lab
- OOP-2: Access Modifiers and Constructors
- OOP-3: Inheritance and Polymorphism
- OOP-4: Interfaces, Abstract Classes
- Concurrency-1: Introduction to Processes and Threads
- Concurrency-2: Executors and Callables
- Concurrency-3: Introduction to Synchronization
- Concurrency-4: Synchronization with Semaphores
- Java Advanced Concepts - 1 [Generics]
- Java Advanced Concepts - 2 [Generics & Collections Lab]
- Java Advanced Concepts - 3 [Streams and Lambdas]
- Java Advanced Concepts - 4 [Exception Handling and Miscellaneous Topics]
- Contest - 1: Java, OOP, and Concurrency
Design Principles & Patterns for Extensible Systems
- SOLID Principles for Extensible Systems with AI integrations
- Design Patterns: Introduction and Singleton
- Design Patterns: Builder
- Design Patterns: Prototype and Registry
- Design Patterns: Leveraging Factory Pattern for Service Abstraction (APIs & AI Services)
- Design Patterns: Adapter and Facade
- Design Patterns: Decorator and Flyweight
- Design Patterns: Behavioural Design Patterns
- UML Diagrams
- Contest - 2: Design Principles & Design Patterns
Applied Design & Machine Coding
- How to Approach Design Problems
- Design TicTacToe
- Code TicTacToe 1
- Code TicTacToe 2
- Design Parking Lot
- Code Parking Lot 1
- Design BookMyShow
- Code BookMyShow 1
- Code BookMyShow 2
- Code BookMyShow 3
- Design Splitwise
- Code Splitwise 1
- Code Splitwise 2
- Machine Coding
AI-First Backend Capstone Project Primer
- Intro to Backend Systems & AI-Augmented Development
- Version Control and Git
- Learning Git Commands & AI Dev Tools
- Intro to Spring Framework and Building APIs
- MVC, Requests in Spring and Starting First Microservice (with AI Service Integration)
- Calling 3rd Party APIs & LLM/AI Services
- Intro to Spring Data JPA
- JPA Queries and Repositories
- Unit Testing and Good Practices (including AI-assisted testing)
- Authentication vs Authorization, OAuth2, JWT
- Implementing UserAuthService
- Deploying Backend & AI-Enabled Applications to AWS
AI-First Backend Capstone Project Advance
- RestTemplate, Resilience & Handling Failures in AI/API Systems
- UUIDs and Representing Inheritance
- Mocking and Writing Unit Tests (including AI services)
- Advanced Testing Strategies for Backend Systems
- JWT Generation and Validation
- Authentication - Implementing OAuth 2
- EBS, RDS
- VPC, Security Groups, Route 53
- Implementing Search: Paging, Sorting & Intro to Semantic Search
- Creating Payment Microservice
- Implementing Stripe PG and Reconciliation
- Optimizing APIs using Redis and Kafka for Async & AI Workloads
- Spring Cloud for Distributed Microservices & AI Services
- Spring Cloud: API Gateway, Load Balancing, Logging & Monitoring
- Docker for Backend & AI Service Deployment
ElectiveBuild a Production-Ready AI-Enabled System
- Module Introduction - Intro to LLMs for Backend Engineers & Prompt
- Engineering for Backend APIs
- Building BookMyShow Chat Agent - 1
- Building BookMyShow Chat Agent - 2
- Building BookMyShow Chat Agent - 3
- Buildng Splitwise AI Receipt Processor - 1
- Buildng Splitwise AI Receipt Processor - 2
- Buildng Splitwise AI Receipt Processor - 3
- Backend Capstone Project: Contest
Fullstack
Web Platform Foundations & UI Systems
- How the Web Works: Browsers, HTML, Developer Tools, and AI Inspection
- Semantic HTML, Forms, and Structured User Input
- CSS Foundations: Cascade, Selectors, Box Model, and Units
- Layout Systems I: Display, Positioning, and Flexbox
- Layout Systems II: Responsive Design, Media Queries, and Grid
- CSS Variables, Transitions, and Visual Polish
- UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
- From Design to Code: AI-Assisted UI Build, Review, and Refinement
- HTML & CSS Certification Contest
JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
- JavaScript Foundations: Values, Types, Variables, Control Flow, and Basic Programming
- Execution Model: Scope, Hoisting, and How JavaScript Runs Closures, Lexical Scope, and Persistent State
- Runtime Reasoning Lab: Predicting Output, Tracing Execution, and Debugging
- Functional JavaScript: Functions, Callbacks, and Higher Order Thinking
- The Browser as a Runtime: DOM Structure and Browser APIs
- Event Systems: User Interaction, Handlers, and UI Behavior
- Product Lab I: Realtime Weather App, JSON, APIs, Async Flow, and Rendering
- Product Lab II: Kanban Board, Product Breakdown, UI Structure, and State Model
- Product Lab III: Kanban Board, DOM Manipulation and Dynamic Rendering
- Product Lab IV: Kanban Board, Business Logic, Persistence, and Local Storage
- Product Lab V: Kanban Board, Edge Cases, UX Refinement, and Extensibility
- Async Systems I: Callbacks, Web APIs, and Non Blocking Execution
- Async Systems II: Promises, Microtasks, and Chained Control Flow
- Async Systems III: Async Await, Error Handling, and Resilient Flows
- Async Systems IV: Promise Combinators, Coordination, and Real World Async Patterns
- Async Debugging Lab: Race Conditions, Failure States, and AI Assisted Investigation
- Browser Event Flow: Bubbling, Capturing, and Propagation
- Interaction Patterns Lab: Event Delegation, Scalable UI Behavior, and Machine Coding
- Performance Patterns Lab: Debouncing, Throttling, and Efficient Frontend Flows
- Object Model I: this, Method Context, and Function Invocation
- JS Certification Contest
React and Frontend Product Architecture Fundamentals
- React Foundations: Components, JSX and Thinking in UI Trees
- React Tooling and TypeScript Setup: Build Tools, JSX, TS Basics and Project Structure
- Props, Lists, Forms and Typed Component Composition
- State, Events and Interactive UI in React
- Lifting State Up, useEffect and Data Flow in Component Trees
- Product Lab 1: IMDB App: App Setup, Routing and Frontend Structure
- Product Lab 2: IMDB App: Movies Page, Pagination and Data Rendering
- Product Lab 3: IMDB App : API Integration, Watchlist and Local Storage
- Product Lab 4: IMDB App : Search, Sorting, Filtering and Shared State
- Context API, State Sharing and Component Communication
- Redux Foundations: Store Design, Actions and Predictable State
- Redux Integration Lab: Product Scale State Management in React
- React Certification Contest
Backend Product Systems, APIs and Production Engineering
- Backend Foundations: Node.js, APIs, Express and Service Thinking
- Data Systems: MongoDB, Mongoose, Schema Design and SQL vs NoSQL Thinking
- Middleware, Validation and MVC for Scalable Backend Structure
- Product Lab 1: Backend Architecture, Domain Modeling and Project Setup
- Product Lab 2: Authentication, Authorization and Role Based Access
- Product Lab 3: Protected Routes, Tokens and Session Aware Flows
- Product Lab 4: Movies, Theatres and Show APIs
- Product Lab 5: Partner Workflows, Admin Approval and Moderated Actions
- Product Lab 6: Booking Flow, Seat Management and Transaction Safety
- Product Lab 7: Payments, Ticket Generation and Order Lifecycle
- Product Lab 8: Email Workflows, Password Reset and User Communication
- Realtime Backend Systems: WebSockets, Live Updates and Event Driven Flows
- MERN Certification Contest
ElectiveBackend Product Systems - Deep Dive
- Backend Quality Lab: API Testing, Debugging and Error Handling
- Backend Security Lab: Validation, Auth Hardening, Abuse Prevention and Safe Defaults
- Production Readiness: Environment Management, Deployment, Logging and Docker Basics
- Scalability Lab: Caching, Queues, Background Jobs and Data Flow Trade Offs
- AI Feature Integration Lab: LLM APIs, Structured Responses and Backend Orchestration
- Architecture and Interview Lab: Backend Design, Trade Offs and AI Assisted Review
ElectiveFoundations of AI-Assisted Full-Stack Development
- Full-Stack Development in the Age of AI
- AI Coding Tools for Full-Stack Builders
- Prompting for UI, Logic, APIs, and Debugging
- Reviewing and Validating AI-Generated Full-Stack Code
- From Screen to Server: AI-Assisted Development Workflows
- Building Faster Without Losing Fundamentals
ElectiveJavaScript Object System & Engineering Patterns
- Object Model II: Classes, Constructors, and Object Oriented Modeling
- Object Model III: Prototypes, Inheritance, and Reusable Behavior
- JavaScript Engineering Lab: Call, Apply, Bind, and Polyfill Thinking
- Polyfills Lab: Higher Order Methods and Implementation Reasoning
- Data Handling Lab: Deep Copy, Shallow Copy, and Reference Behavior
ElectiveReact, TypeScript and Frontend Product Architecture Deep Dive
- TypeScript Foundations for JavaScript Developers
- Advanced Hooks: useRef, useMemo, useCallback and useReducer
- Custom Hooks and Reusable Logic Patterns
- React Performance Lab: Rendering, Memoization and UI Efficiency
- Machine Coding Lab: Component Design, State Design and Real UI Problem Solving
- Architecture Studio: React Patterns, State Trade Offs and AI Assisted Review
- Next.js Foundations: App Router, Layouts and Modern React Delivery
- Next.js Data Fetching: Server and Client Components, Rendering Strategy and SEO
- Next.js Product Lab: Forms, Route Handlers, Auth Flow and Deployment
- Advanced React Systems: Fiber, Concurrent Rendering, Suspense, Lazy Loading and Error Boundaries
- React Interview and Frontend Reasoning Lab
Forward Deployed Engineer (FDE)
FDE Foundations: Python, Workflow & Delivery
- The FDE Role: Customer-Embedded Engineering
- Problem Discovery & Solution Thinking for FDEs
- Python Toolchain & Environment Setup (pyenv, uv, ruff, mypy)
- Iterators, Generators & Comprehensions
- Closures, Decorators & Context Managers
- OOP, Concurrency & Async Python
- Pydantic v2, Structured Logging & Profiling
- Git Internals, GitHub Workflows & AI Dev Tools (Cursor, Claude Code, MCP)
- Testing: pytest, Property-Based Testing & CI
- Software Engineering Best Practices (SOLID, Hexagonal Architecture)
- Linux, Shell & Scripting for FDEs
- Assessment: Python Engineering Challenge
Backend Engineering, Observability & Advanced Data Systems
- Introduction to Backend Engineering — HTTP, REST & API Design
- FastAPI: Intro to Deep Dive
- Auth: OAuth2, JWT, OIDC & RBAC
- Building an Order Management Module & its API
- Building Payments & Notifications (Stripe, Celery)
- Building the Demo Frontend
- Real-Time, Queues & Caching (WebSockets, SSE, Redis)
- Observability & Distributed Tracing (OpenTelemetry, Grafana)
- Postgres Advanced: JSONB, Full-Text Search & pgvector
- Postgres Internals: EXPLAIN ANALYZE, Indexing & MVCC
- NoSQL, Document DBs & Vector Databases
- Dimensional Modeling, dbt & Modern Data Stack
- Workflow Orchestration with Airflow & Data Quality
- Event-Driven Architecture & Kafka Fundamentals
- Assessment: Data Pipeline Build & Debug
Full-Stack FDE: TypeScript, React & AI-First Frontends
- TypeScript Fundamentals for Python Engineers
- React Essentials for AI Apps
- Next.js for Full-Stack AI Apps
- Vercel AI SDK & Streaming UIs
- AI Product UX & Customer-Facing Polish
Cloud, DevOps, Kubernetes & Infrastructure
- AWS Core: IAM, VPC & Networking
- Compute, Storage & Managed Services (EC2, S3, RDS, SQS)
- AWS Security & Secrets Management (KMS, Secrets Manager, CloudTrail)
- Docker: Production Containers
- Kubernetes Architecture & Core Concepts
- EKS, Helm & Production Kubernetes
- Kubernetes Networking, Security & GPU Workloads
- CI/CD Pipelines & GitOps (GitHub Actions, ArgoCD)
- Terraform & Infrastructure as Code
- Serverless & Event-Driven Cloud (Lambda, API Gateway, Step Functions)
- SRE & Reliability Engineering for FDEs
- Assessment: Deploy, Break, Fix on Cloud
Enterprise Communication, Consulting & LLM Engineering
- Customer Discovery & Requirements Gathering
- Technical Scoping & Solution Documentation (PRD-lite, options matrix, risk register)
- Stakeholder Communication & Written Artifacts
- Demo Storytelling & Handling Pushback
- LLM Fundamentals for Production
- Prompt Engineering for Production Systems
- RAG Architecture: Ingestion & Retrieval
- RAG over Customer Documents & Hybrid Search
- RAG Evaluation & Iteration (RAGAS)
- LLM Safety, Guardrails & Security
- Cost, Latency & Model Routing
- Assessment: Discovery Call + RAG PoC Build
Agentic Systems & Enterprise Integrations
- Tool Calling, Function Calling & Structured Output
- Agentic Patterns & Production Concerns
- Agent Debugging, Failure Analysis & Evaluation
- MCP & Enterprise Tooling
- Multi-Agent Patterns & Human-in-the-Loop
- Assessment: Agentic System Build & Red-Team
- Enterprise Systems Landscape & Integration Topology
- API Integration Patterns & Connector Design
- Integration Failure Modes & Debugging
- Messy Customer Data & Entity Resolution
- Build: CRM-to-AI Support Copilot
- Assessment: Integration War Room
Application Engineering, Security & Reliability
- Product Thinking & Architecture for FDE Apps
- Frontend Essentials for FDEs: React + TypeScript
- Multi-Tenant Design & Background Workflows (Postgres RLS, Celery)
- Document Processing & AI Extraction Workflows
- Build: Enterprise Document Review App
- Developer Experience & API Documentation
- Enterprise Security for FDE Systems (PII, SOC2, GDPR)
- Secrets, Encryption & Deployment Topologies
- Load Testing, Capacity Planning & Performance (k6)
- Incident Response & Customer-Facing RCA
- Enterprise Readiness Checklist & Go-Live
- Assessment: Secure Deploy + Incident Simulation
System Design, Capstone & Hiring Readiness
- Distributed Systems Fundamentals (CAP, PACELC, Raft, Saga)
- System Design: RAG System at Scale
- System Design: Agentic Platform at Scale
- System Design: Multi-Tenant SaaS Platform
- System Design: Enterprise Integration Hub
- System Design Interview Framework & Practice
- Capstone Sprint 1: Discovery & Solution Design
- Capstone Sprint 2: Core Build & Integration Layer
- Capstone Sprint 3: Harden, Secure & Observe
- Capstone Sprint 4: Red-Team, Eval & Fix
- Capstone Demo Day: Client Panel Presentation
- Interview Readiness & Career Launch
- FDE Mock Engagement: Full Simulation
- Graduation Review: Portfolio Defense & Next Steps
Elective Containerization and Orchestration
- Docker introduction
- Docker image and Docker containers
- Building your own Docker image
- Image and Containers Deep Dive
- Docker volume
- Docker networking deep dive
- Hardening the Docker env. (DevSecOps)
- Demo of implementing industry standard implementation (e.g. in image hardening and other security standards)
- Introduction to Orchestration
- Kubernetes architecture
- Kubernetes Pod deep dive
- Kubernetes Replicaset and Deployment deep dive, side car
- Kubernetes networking
- Scaling options in kubernetes - HPA, CA and VPA - compare with Karpentor
- Introduction to scaling in kubernets, Network policies
- Kubernetes security - RBAC (DevSecOps)
- Kubernetes volumes
Elective AWS : multi-region cloud deep dive
- AWS VPC & Networking Basics
- Advanced AWS Networking
- AWS Observability & CloudWatch
- CloudWatch & CloudTrail Advanced (DevSecOps)
- Docker App on EC2 Project
- AWS Lambda & API Gateway
- End-to-End Project day
- AWS ECS & ECR Intro
- ECS Fundamental
- EKS Basics
- EKS Advanced
- EKS Security & Operations
- Microservices on AWS Project
- Microservices Project – Phase 2
- AWS Security: Identity & Network (DevSecOps)
- AWS Security: Data & Detection (DevSecOps)
- AWS Security Hands-on (DevSecOps)
Elective Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance
- Architect the Storage for an Application
- Data Lifecycle Management and Storage Optimization
- Backup and Disaster Recovery Strategies
- Designing the Networking of an Application
- Load Balancing and Auto Scaling Groups
- Designing for scalability of application and data
- Database Sharding Strategies and Hot-Spot Mitigation
- Edge Caching, CDNs, and Latency Reduction
- Microservices Performance — Latency, Throughput, Concurrency
- Designing for High Availability — Multi-Region Active-Active
- Fault Tolerance Engineering — Circuit Breakers, Retries, Backoff
- Graceful Degradation — Rate Limiting, Throttling, Shedding
- Data Consistency Trade-offs — CAP, PACELC
System Design
Distributed System Design & AI-Integrated Architectures
- System Design Foundations & Modern Infrastructure
- Load Balancing, Consistent Hashing & Traffic Routing at Scale
- Caching Systems: CDN, Backend Caches, Cache Invalidation
- Case Study: Caching at Scale (Scaler Code Judge and Contest Leaderboards + AI Workloads)
- Case Study: Caching Facebook News Feed
- CAP / PACELC theorem + Master Slave Replication
- SQL vs NoSQL + Sharding
- Database Orchestration & Shard Creation
- Case study: Google Typeahead (How to approach System Design Problems)
- Case Study: Google Typeahead (Design and Optimizations)
- NoSQL Internals - LSM Tree and Multi Master
- Case Study: Messaging Apps (FB Messenger, Whatsapp, Slack)
- Messaging Queues - Apache Kafka & Zookeeper
- Case Study: ElasticSearch (Full Text Search)
- Case Study: S3, HDFS (Large File Storage)
- Case Study: Uber (Nearest Neighbor Search)
- Case Study: Rate Limiter + Unique ID Generator (Infra)
- Case Study: OTT Platform (OTT)
- Microservices - 1
- Microservices - 2
- Case Study: Ecommerce Platform (Microservices)
Interview Preparation
Mastering LastMile - Interview Simulation
- DSA Interview Simulation: Problem Solving & Thinking Under Pressure
- LLD Interview Simulation: Structuring Scalable Solutions
- HLD Interview Simulation: Designing Systems & Communicating Trad
Data Engineering
Data Engineering
- Introduction to Data Engineering
- Writing Efficient Queries: Part 1
- Writing Efficient Queries: Part 2
- Intro to Hadoop
- HDFS and MAP-REDUCE
- Introduction to Hive
- Advanced features of Hive
- Basics of Spark
- Spark Programming
- Structured API - PySpark
- PySpark Operations
- Introduction to Streaming
- Apache Spark Streaming
- Advanced Spark Streaming
- Additional Streaming Services: Bringing it all together
- Modern Data Architecures
- AWS Services for Data Engineering
- Data Modelling
- Orchestrating data pipelines
- Orchestration Continued
- Distributed Coordination
- Load Balancing
- Data Pillars
- Capstone
Advanced DSA
DSA Edge: Advanced Patterns & Interview Techniques
- DSA Edge : Townhall
- DSA Edge : Townhall (Post-SQL - change name after scheduling)
- Revision of DSA Topics
- Maths: Inverse Mod & Problems
- Backtracking: Famous Problems
- Tries 1: Trie of Character
- Tries 2: Trie of Bits + Problems on Trees
- Strings Pattern Matching
- DP 1: DP on Strings
- DP 2: Famous Problems
- Graphs 1: Bipartite Graph
- Graphs 2: Belleman Ford & Floyd Warshall Algorithm
- Advanced Interview Problems
- DSA Edge Mandatory Contest: Full Syllabus
- DSA Edge Full Syllabus: Contest Discussion
Product Management for Engineers
- Townhall: Product Management
- Introduction to Product Management 1
- Understanding the Product Lifecycle 1
- Understanding the Product Lifecycle 2
- Critical Thinking in Product Development 1
- Critical Thinking in Product Development 2
- Market Structure Analysis and Its Technical Aspects 1
- Market Structure Analysis and Its Technical Aspects 2
- MVPs, Prototyping, and Growth Hacking 1
- MVPs, Prototyping, and Growth Hacking 2
- Concept Development, Validation, and the Role of Developers 1
- Concept Development, Validation, and the Role of Developers 2
- Introduction to Product Analytics 1
Gen AI for Software Engineers
- Introduction to AI Engineering
- Refresher: Modern Text & Image AI Model Architectures
- Getting started with Text Generation LLM APIs (OpenAI API)
- Designing Eval Pipelines for AI Apps and Observability
- Prompt Engineering: Introduction
- Retrieval-Augmented Generation (RAG) Introduction
- Embeddings Deep Dive
- Multimodal & Tabular RAG
- Prompt Engineering: Security
- Agents: Foundations & Planning
- Advanced Agent Concepts
- Agent: Frameworks and Protocols
- Fine Tuning Existing Models
- Audio, Image, Video, Expressions: AI Modalities
- Scaling AI Applications
- Model Quantization Techniques
- Advanced Fine Tuning Techniques
- Dataset Engineering & Inference Optimization
Intermediate
Programming Fundamentals
Intermediate DSA : AI Assisted Problem Solving
- Time Complexity
- Introduction to Arrays & Basics of AI
- Lab Session on TC, SC, Output & Debugging
- Arrays: Prefix Sum & Carry Forward with AI-Assisted Problem Solving
- Lab Session on Prefix Sum & Carry Forward
- Arrays: Arrays techniques & smart prompting
- Lab Session on Memory Management & Sorting Basics
- Bit Manipulations Basics
- Lab Session on 2D Matrices
- Strings & Immutability visualisations through AI
- Lab on Matrix & Strings using AI
- Contest
Agentic AI
AI & Agents: From Talking to AI to Building One
- GenAI World & LLM Landscape
- Prompt Engineering Basics
- Advanced Prompting & AI Safety Basics
- LLM Built-in Power Tools
- RAG
- n8n Automation Workflow
- What Is an AI Agent?
- Building Agents with n8n
- OpenClaw: Personal 24/7 AI Agent
- Multi-Agent Systems
- Debugging AI
Advanced DSA
Advanced DSA: Foundations:Core Techniques & Optimization
- Time Complexity
- Arrays Techniques
- Arrays 1: One Dimensional
- Arrays 2: Two Dimensional
- Lab Session on Arrays
- Bit Manipulation
- Lab Session on Bit Manipulation
- Recursion
- Lab Session on Recursion
- Maths: Modular Arithmetic & GCD
- Hashing
- Lab Session on Hashing
- Sorting 1: Count Sort & Merge Sort
- Sorting 2: Quick Sort & Comparator Problems
- Sample Contest: Dual Camera Proctoring
- Contest 1: Arrays, Bit Manipulation, Recursion, Math, Hashing & Sorting
Advanced DSA: Linear & Non-Linear Structures
- Searching 1: Binary Search on Array
- Searching 2: Binary Search on Answer
- Lab Session on Searching
- Classes, Objects & Linked List Introduction
- Linked List: Basic Problems
- Stacks
- Lab Session on Stacks
- Queues: Implementation & Problems
- Trees 1: Structure & Traversal
- Trees 2: BST
- Lab Session on Binary Trees
- Revision of DSA 1 & 2
- Break
- Contest 2 : Searching, Linked List, Stacks, Queues , Trees & contest discussion
Advanced DSA: Backtracking & Advanced Trees
- Maths: Combinatorics Basics & Prime Numbers
- Lab Session on Prime Numbers & 2 Pointers
- Lab Session on Maths & 2 Pointers
- Backtracking
- Lab Session on Backtracking
- Linked List: Sorting and Problems
- Linked List: Doubly Linked List & Detecting Loop
- Trees 4: Morris Inorder Traversal + LCA
- Lab Session on Binary Trees 2
- Hashing 3: Internal Implementation & Problems
- Contest 3: Math, Two Pointers, Backtracking, Linked List , Trees & contest discussion
Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
- Heaps: Introduction
- Heap Sort & Greedy
- Lab Session on Heaps & Greedy
- Lab Session on Interview Problems 1
- DP 1: One Dimensional
- DP 2: Two Dimensional
- DP 3: Knapsack
- Lab Session on Applications of Knapsack
- Graphs 1: Introduction, DFS & Cycle Detection
- Graphs 2: BFS & MST
- Graphs 3: Dijkstra Algo & Topological Sort
- Lab Session on Interview Problems 2
- Revision of DSA 3 & 4
- Contest 4: Heaps, Greedy, DP & Graphs
- Mandatory Skill Evaluation Test: DSA
- Skill Evaluation Test Discussion + How to ace DSA Interview
- DSA : Real World Project 1 (Social Network Analyzer)
- DSA : Real world Project 2 ( Invoice Merger )
Databases & SQL
Databases & SQL
- Introduction to DBMS & Keys
- CRUD Operations - 1
- CRUD Operations - 2
- Joins
- Aggregate Queries
- Joins and Aggregate Queries Working Session
- Subqueries & Views
- Indexing
- Transactions
- Window Functions
- Schema Design - 1
- Schema Design - 2
- Databases & SQL Contest: SQL and Schema Design
Backend
Foundations of Object-Oriented Design & Scalable Systems
- Intro to LLD for Scalable & AI-Ready Systems
- OOP-1: Intro to OOP Lab
- OOP-2: Access Modifiers and Constructors
- OOP-3: Inheritance and Polymorphism
- OOP-4: Interfaces, Abstract Classes
- Concurrency-1: Introduction to Processes and Threads
- Concurrency-2: Executors and Callables
- Concurrency-3: Introduction to Synchronization
- Concurrency-4: Synchronization with Semaphores
- Java Advanced Concepts - 1 [Generics]
- Java Advanced Concepts - 2 [Generics & Collections Lab]
- Java Advanced Concepts - 3 [Streams and Lambdas]
- Java Advanced Concepts - 4 [Exception Handling and Miscellaneous Topics]
- Contest - 1: Java, OOP, and Concurrency
Design Principles & Patterns for Extensible Systems
- SOLID Principles for Extensible Systems with AI integrations
- Design Patterns: Introduction and Singleton
- Design Patterns: Builder
- Design Patterns: Prototype and Registry
- Design Patterns: Leveraging Factory Pattern for Service Abstraction (APIs & AI Services)
- Design Patterns: Adapter and Facade
- Design Patterns: Decorator and Flyweight
- Design Patterns: Behavioural Design Patterns
- UML Diagrams
- Contest - 2: Design Principles & Design Patterns
Applied Design & Machine Coding
- How to Approach Design Problems
- Design TicTacToe
- Code TicTacToe 1
- Code TicTacToe 2
- Design Parking Lot
- Code Parking Lot 1
- Design BookMyShow
- Code BookMyShow 1
- Code BookMyShow 2
- Code BookMyShow 3
- Design Splitwise
- Code Splitwise 1
- Code Splitwise 2
- Machine Coding
AI-First Backend Capstone Project Primer
- Intro to Backend Systems & AI-Augmented Development
- Version Control and Git
- Learning Git Commands & AI Dev Tools
- Intro to Spring Framework and Building APIs
- MVC, Requests in Spring and Starting First Microservice (with AI Service Integration)
- Calling 3rd Party APIs & LLM/AI Services
- Intro to Spring Data JPA
- JPA Queries and Repositories
- Unit Testing and Good Practices (including AI-assisted testing)
- Authentication vs Authorization, OAuth2, JWT
- Implementing UserAuthService
- Deploying Backend & AI-Enabled Applications to AWS
AI-First Backend Capstone Project Advance
- RestTemplate, Resilience & Handling Failures in AI/API Systems
- UUIDs and Representing Inheritance
- Mocking and Writing Unit Tests (including AI services)
- Advanced Testing Strategies for Backend Systems
- JWT Generation and Validation
- Authentication - Implementing OAuth 2
- EBS, RDS
- VPC, Security Groups, Route 53
- Implementing Search: Paging, Sorting & Intro to Semantic Search
- Creating Payment Microservice
- Implementing Stripe PG and Reconciliation
- Optimizing APIs using Redis and Kafka for Async & AI Workloads
- Spring Cloud for Distributed Microservices & AI Services
- Spring Cloud: API Gateway, Load Balancing, Logging & Monitoring
- Docker for Backend & AI Service Deployment
ElectiveBuild a Production-Ready AI-Enabled System
- Module Introduction - Intro to LLMs for Backend Engineers & Prompt
- Engineering for Backend APIs
- Building BookMyShow Chat Agent - 1
- Building BookMyShow Chat Agent - 2
- Building BookMyShow Chat Agent - 3
- Buildng Splitwise AI Receipt Processor - 1
- Buildng Splitwise AI Receipt Processor - 2
- Buildng Splitwise AI Receipt Processor - 3
- Backend Capstone Project: Contest
Fullstack
Web Platform Foundations & UI Systems
- How the Web Works: Browsers, HTML, Developer Tools, and AI Inspection
- Semantic HTML, Forms, and Structured User Input
- CSS Foundations: Cascade, Selectors, Box Model, and Units
- Layout Systems I: Display, Positioning, and Flexbox
- Layout Systems II: Responsive Design, Media Queries, and Grid
- CSS Variables, Transitions, and Visual Polish
- UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
- From Design to Code: AI-Assisted UI Build, Review, and Refinement
- HTML & CSS Certification Contest
JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
- Full Stack LLD: JS-1: JS Refresher and Code Execution
- Full Stack LLD: JS-2: OOPS-1 : This, Bind, Call, Apply, Inheritance
- Full Stack LLD: JS-3: Polyfills of call,bind ,apply & deep copy-shallow copy
- "Full Stack LLD: JS-4: Array , HOFs and it's Polyfills"
- Full Stack LLD: JS-5: ES6 Classes and Objects
- Full Stack LLD: JS-6: Closure and It's application
- Full Stack LLD: JS-7: OOPS-2 : Object creation, Freezing objects
- Full Stack LLD: JS-8: Event loop and Callback
- Full Stack LLD: JS-9: Promises and MicroTask Queue
- Full Stack LLD: JS-10: Promise chaining and Imp polyfills
- Full Stack LLD: JS-11: Async await & Error handling
- Full Stack LLD: JS-12: ES6 DataTypes and Modules
- Full Stack LLD: FE Machine coding-1:Intro to the DOM
- Full Stack LLD: FE Machine coding-2: Events & Event Handling, Bubbling & capturing
- Full Stack LLD & Projects Certification Contest - JavaScript
React and Frontend Product Architecture Fundamentals
- React Foundations: Components, JSX and Thinking in UI Trees
- React Tooling and TypeScript Setup: Build Tools, JSX, TS Basics and Project Structure
- Props, Lists, Forms and Typed Component Composition
- State, Events and Interactive UI in React
- Lifting State Up, useEffect and Data Flow in Component Trees
- Product Lab 1: IMDB App: App Setup, Routing and Frontend Structure
- Product Lab 2: IMDB App: Movies Page, Pagination and Data Rendering
- Product Lab 3: IMDB App : API Integration, Watchlist and Local Storage
- Product Lab 4: IMDB App : Search, Sorting, Filtering and Shared State
- Context API, State Sharing and Component Communication
- Redux Foundations: Store Design, Actions and Predictable State
- Redux Integration Lab: Product Scale State Management in React
- React Certification Contest
Backend Product Systems, APIs and Production Engineering
- Backend Foundations: Node.js, APIs, Express and Service Thinking
- Data Systems: MongoDB, Mongoose, Schema Design and SQL vs NoSQL Thinking
- Middleware, Validation and MVC for Scalable Backend Structure
- Product Lab 1: Backend Architecture, Domain Modeling and Project Setup
- Product Lab 2: Authentication, Authorization and Role Based Access
- Product Lab 3: Protected Routes, Tokens and Session Aware Flows
- Product Lab 4: Movies, Theatres and Show APIs
- Product Lab 5: Partner Workflows, Admin Approval and Moderated Actions
- Product Lab 6: Booking Flow, Seat Management and Transaction Safety
- Product Lab 7: Payments, Ticket Generation and Order Lifecycle
- Product Lab 8: Email Workflows, Password Reset and User Communication
- Realtime Backend Systems: WebSockets, Live Updates and Event Driven Flows
Backend Product Systems - Deep Dive
- Backend Quality Lab: API Testing, Debugging and Error Handling
- Backend Security Lab: Validation, Auth Hardening, Abuse Prevention and Safe Defaults
- Production Readiness: Environment Management, Deployment, Logging and Docker Basics
- Scalability Lab: Caching, Queues, Background Jobs and Data Flow Trade Offs
- AI Feature Integration Lab: LLM APIs, Structured Responses and Backend Orchestration
- Architecture and Interview Lab: Backend Design, Trade Offs and AI Assisted Review
- MERN Certification Contest
ElectiveFoundations of AI-Assisted Full-Stack Development
- Full-Stack Development in the Age of AI
- AI Coding Tools for Full-Stack Builders
- Prompting for UI, Logic, APIs, and Debugging
- Reviewing and Validating AI-Generated Full-Stack Code
- From Screen to Server: AI-Assisted Development Workflows
- Building Faster Without Losing Fundamentals
ElectiveFrontend Systems & Machine Coding Mastery
- Full Stack LLD: FE Machine coding: Case Studies
- Full Stack LLD: FE Machine coding: Browser Perf & Memory leaks
- Full Stack LLD: FE Machine coding: HTTP and network Optimization
- Full Stack LLD: FE Machine coding:- Typeahead[Intersection Obs, Debouncing, Throttling]
- Full Stack LLD: FE Machine coding: - Kanban board-1
- Full Stack LLD: FE Machine coding: Kanban board-2
- Full Stack LLD & Projects: Contest - FE Machine Coding
ElectiveReact, TypeScript and Frontend Product Architecture Deep Dive
- TypeScript Foundations for JavaScript Developers
- Advanced Hooks: useRef, useMemo, useCallback and useReducer
- Custom Hooks and Reusable Logic Patterns
- React Performance Lab: Rendering, Memoization and UI Efficiency
- Machine Coding Lab: Component Design, State Design and Real UI Problem Solving
- Architecture Studio: React Patterns, State Trade Offs and AI Assisted Review
- Next.js Foundations: App Router, Layouts and Modern React Delivery
- Next.js Data Fetching: Server and Client Components, Rendering Strategy and SEO
- Next.js Product Lab: Forms, Route Handlers, Auth Flow and Deployment
- Advanced React Systems: Fiber, Concurrent Rendering, Suspense, Lazy Loading and Error Boundaries
- React Interview and Frontend Reasoning Lab
Forward Deployed Engineer (FDE)
FDE Foundations: Python, Workflow & Delivery
- The FDE Role: Customer-Embedded Engineering
- Problem Discovery & Solution Thinking for FDEs
- Python Toolchain & Environment Setup (pyenv, uv, ruff, mypy)
- Iterators, Generators & Comprehensions
- Closures, Decorators & Context Managers
- OOP, Concurrency & Async Python
- Pydantic v2, Structured Logging & Profiling
- Git Internals, GitHub Workflows & AI Dev Tools (Cursor, Claude Code, MCP)
- Testing: pytest, Property-Based Testing & CI
- Software Engineering Best Practices (SOLID, Hexagonal Architecture)
- Linux, Shell & Scripting for FDEs
- Assessment: Python Engineering Challenge
Backend Engineering, Observability & Advanced Data Systems
- Introduction to Backend Engineering — HTTP, REST & API Design
- FastAPI: Intro to Deep Dive
- Auth: OAuth2, JWT, OIDC & RBAC
- Building an Order Management Module & its API
- Building Payments & Notifications (Stripe, Celery)
- Building the Demo Frontend
- Real-Time, Queues & Caching (WebSockets, SSE, Redis)
- Observability & Distributed Tracing (OpenTelemetry, Grafana)
- Postgres Advanced: JSONB, Full-Text Search & pgvector
- Postgres Internals: EXPLAIN ANALYZE, Indexing & MVCC
- NoSQL, Document DBs & Vector Databases
- Dimensional Modeling, dbt & Modern Data Stack
- Workflow Orchestration with Airflow & Data Quality
- Event-Driven Architecture & Kafka Fundamentals
- Assessment: Data Pipeline Build & Debug
Full-Stack FDE: TypeScript, React & AI-First Frontends
- TypeScript Fundamentals for Python Engineers
- React Essentials for AI Apps
- Next.js for Full-Stack AI Apps
- Vercel AI SDK & Streaming UIs
- AI Product UX & Customer-Facing Polish
Cloud, DevOps, Kubernetes & Infrastructure
- AWS Core: IAM, VPC & Networking
- Compute, Storage & Managed Services (EC2, S3, RDS, SQS)
- AWS Security & Secrets Management (KMS, Secrets Manager, CloudTrail)
- Docker: Production Containers
- Kubernetes Architecture & Core Concepts
- EKS, Helm & Production Kubernetes
- Kubernetes Networking, Security & GPU Workloads
- CI/CD Pipelines & GitOps (GitHub Actions, ArgoCD)
- Terraform & Infrastructure as Code
- Serverless & Event-Driven Cloud (Lambda, API Gateway, Step Functions)
- SRE & Reliability Engineering for FDEs
- Assessment: Deploy, Break, Fix on Cloud
Enterprise Communication, Consulting & LLM Engineering
- Customer Discovery & Requirements Gathering
- Technical Scoping & Solution Documentation (PRD-lite, options matrix, risk register)
- Stakeholder Communication & Written Artifacts
- Demo Storytelling & Handling Pushback
- LLM Fundamentals for Production
- Prompt Engineering for Production Systems
- RAG Architecture: Ingestion & Retrieval
- RAG over Customer Documents & Hybrid Search
- RAG Evaluation & Iteration (RAGAS)
- LLM Safety, Guardrails & Security
- Cost, Latency & Model Routing
- Assessment: Discovery Call + RAG PoC Build
Agentic Systems & Enterprise Integrations
- Tool Calling, Function Calling & Structured Output
- Agentic Patterns & Production Concerns
- Agent Debugging, Failure Analysis & Evaluation
- MCP & Enterprise Tooling
- Multi-Agent Patterns & Human-in-the-Loop
- Assessment: Agentic System Build & Red-Team
- Enterprise Systems Landscape & Integration Topology
- API Integration Patterns & Connector Design
- Integration Failure Modes & Debugging
- Messy Customer Data & Entity Resolution
- Build: CRM-to-AI Support Copilot
- Assessment: Integration War Room
Application Engineering, Security & Reliability
- Product Thinking & Architecture for FDE Apps
- Frontend Essentials for FDEs: React + TypeScript
- Multi-Tenant Design & Background Workflows (Postgres RLS, Celery)
- Document Processing & AI Extraction Workflows
- Build: Enterprise Document Review App
- Developer Experience & API Documentation
- Enterprise Security for FDE Systems (PII, SOC2, GDPR)
- Secrets, Encryption & Deployment Topologies
- Load Testing, Capacity Planning & Performance (k6)
- Incident Response & Customer-Facing RCA
- Enterprise Readiness Checklist & Go-Live
- Assessment: Secure Deploy + Incident Simulation
System Design, Capstone & Hiring Readiness
- Distributed Systems Fundamentals (CAP, PACELC, Raft, Saga)
- System Design: RAG System at Scale
- System Design: Agentic Platform at Scale
- System Design: Multi-Tenant SaaS Platform
- System Design: Enterprise Integration Hub
- System Design Interview Framework & Practice
- Capstone Sprint 1: Discovery & Solution Design
- Capstone Sprint 2: Core Build & Integration Layer
- Capstone Sprint 3: Harden, Secure & Observe
- Capstone Sprint 4: Red-Team, Eval & Fix
- Capstone Demo Day: Client Panel Presentation
- Interview Readiness & Career Launch
- FDE Mock Engagement: Full Simulation
- Graduation Review: Portfolio Defense & Next Steps
Elective Containerization and Orchestration
- Docker introduction
- Docker image and Docker containers
- Building your own Docker image
- Image and Containers Deep Dive
- Docker volume
- Docker networking deep dive
- Hardening the Docker env. (DevSecOps)
- Demo of implementing industry standard implementation (e.g. in image hardening and other security standards)
- Introduction to Orchestration
- Kubernetes architecture
- Kubernetes Pod deep dive
- Kubernetes Replicaset and Deployment deep dive, side car
- Kubernetes networking
- Scaling options in kubernetes - HPA, CA and VPA - compare with Karpentor
- Introduction to scaling in kubernets, Network policies
- Kubernetes security - RBAC (DevSecOps)
- Kubernetes volumes
Elective AWS : multi-region cloud deep dive
- AWS VPC & Networking Basics
- Advanced AWS Networking
- AWS Observability & CloudWatch
- CloudWatch & CloudTrail Advanced (DevSecOps)
- Docker App on EC2 Project
- AWS Lambda & API Gateway
- End-to-End Project day
- AWS ECS & ECR Intro
- ECS Fundamental
- EKS Basics
- EKS Advanced
- EKS Security & Operations
- Microservices on AWS Project
- Microservices Project – Phase 2
- AWS Security: Identity & Network (DevSecOps)
- AWS Security: Data & Detection (DevSecOps)
- AWS Security Hands-on (DevSecOps)
Elective Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance
- Architect the Storage for an Application
- Data Lifecycle Management and Storage Optimization
- Backup and Disaster Recovery Strategies
- Designing the Networking of an Application
- Load Balancing and Auto Scaling Groups
- Designing for scalability of application and data
- Database Sharding Strategies and Hot-Spot Mitigation
- Edge Caching, CDNs, and Latency Reduction
- Microservices Performance — Latency, Throughput, Concurrency
- Designing for High Availability — Multi-Region Active-Active
- Fault Tolerance Engineering — Circuit Breakers, Retries, Backoff
- Graceful Degradation — Rate Limiting, Throttling, Shedding
- Data Consistency Trade-offs — CAP, PACELC
System Design
Distributed System Design & AI-Integrated Architectures
- System Design Foundations & Modern Infrastructure
- Load Balancing, Consistent Hashing & Traffic Routing at Scale
- Caching Systems: CDN, Backend Caches, Cache Invalidation
- Case Study: Caching at Scale (Scaler Code Judge and Contest Leaderboards + AI Workloads)
- Case Study: Caching Facebook News Feed
- CAP / PACELC theorem + Master Slave Replication
- SQL vs NoSQL + Sharding
- Database Orchestration & Shard Creation
- Case study: Google Typeahead (How to approach System Design Problems)
- Case Study: Google Typeahead (Design and Optimizations)
- NoSQL Internals - LSM Tree and Multi Master
- Case Study: Messaging Apps (FB Messenger, Whatsapp, Slack)
- Messaging Queues - Apache Kafka & Zookeeper
- Case Study: ElasticSearch (Full Text Search)
- Case Study: S3, HDFS (Large File Storage)
- Case Study: Uber (Nearest Neighbor Search)
- Case Study: Rate Limiter + Unique ID Generator (Infra)
- Case Study: OTT Platform (OTT)
- Microservices - 1
- Microservices - 2
- Case Study: Ecommerce Platform (Microservices)
Interview Preparation
Mastering LastMile - Interview Simulation
- DSA Interview Simulation: Problem Solving & Thinking Under Pressure
- LLD Interview Simulation: Structuring Scalable Solutions
- HLD Interview Simulation: Designing Systems & Communicating Trad
Data Engineering
Data Engineering
- Introduction to Data Engineering
- Writing Efficient Queries: Part 1
- Writing Efficient Queries: Part 2
- Intro to Hadoop
- HDFS and MAP-REDUCE
- Introduction to Hive
- Advanced features of Hive
- Basics of Spark
- Spark Programming
- Structured API - PySpark
- PySpark Operations
- Introduction to Streaming
- Apache Spark Streaming
- Advanced Spark Streaming
- Additional Streaming Services: Bringing it all together
- Modern Data Architecures
- AWS Services for Data Engineering
- Data Modelling
- Orchestrating data pipelines
- Orchestration Continued
- Distributed Coordination
- Load Balancing
- Data Pillars
- Capstone
Advanced DSA
DSA Edge: Advanced Patterns & Interview Techniques
- DSA Edge : Townhall
- DSA Edge : Townhall (Post-SQL - change name after scheduling)
- Revision of DSA Topics
- Maths: Inverse Mod & Problems
- Backtracking: Famous Problems
- Tries 1: Trie of Character
- Tries 2: Trie of Bits + Problems on Trees
- Strings Pattern Matching
- DP 1: DP on Strings
- DP 2: Famous Problems
- Graphs 1: Bipartite Graph
- Graphs 2: Belleman Ford & Floyd Warshall Algorithm
- Advanced Interview Problems
- DSA Edge Mandatory Contest: Full Syllabus
- DSA Edge Full Syllabus: Contest Discussion
Product Management for Engineers
- Townhall: Product Management
- Introduction to Product Management 1
- Understanding the Product Lifecycle 1
- Understanding the Product Lifecycle 2
- Critical Thinking in Product Development 1
- Critical Thinking in Product Development 2
- Market Structure Analysis and Its Technical Aspects 1
- Market Structure Analysis and Its Technical Aspects 2
- MVPs, Prototyping, and Growth Hacking 1
- MVPs, Prototyping, and Growth Hacking 2
- Concept Development, Validation, and the Role of Developers 1
- Concept Development, Validation, and the Role of Developers 2
- Introduction to Product Analytics 1
Gen AI for Software Engineers
- Introduction to AI Engineering
- Refresher: Modern Text & Image AI Model Architectures
- Getting started with Text Generation LLM APIs (OpenAI API)
- Designing Eval Pipelines for AI Apps and Observability
- Prompt Engineering: Introduction
- Retrieval-Augmented Generation (RAG) Introduction
- Embeddings Deep Dive
- Multimodal & Tabular RAG
- Prompt Engineering: Security
- Agents: Foundations & Planning
- Advanced Agent Concepts
- Agent: Frameworks and Protocols
- Fine Tuning Existing Models
- Audio, Image, Video, Expressions: AI Modalities
- Scaling AI Applications
- Model Quantization Techniques
- Advanced Fine Tuning Techniques
- Dataset Engineering & Inference Optimization
Advanced
Agentic AI
AI & Agents: From Talking to AI to Building One
- The runway to AI
- GenAI World & LLM Landscape
- Prompt Engineering Basics
- Advanced Prompting & AI Safety Basics
- LLM Built-in Power Tools
- RAG
- n8n Automation Workflow
- What Is an AI Agent?
- Building Agents with n8n
- OpenClaw: Personal 24/7 AI Agent
- Multi-Agent Systems
- Debugging AI with Vibecoding Tools
Advanced DSA
Advanced DSA: Foundations:Core Techniques & Optimization
- Time Complexity
- Arrays Techniques
- Arrays 1: One Dimensional
- Arrays 2: Two Dimensional
- Lab Session on Arrays
- Bit Manipulation
- Lab Session on Bit Manipulation
- Recursion
- Lab Session on Recursion
- Maths: Modular Arithmetic & GCD
- Hashing
- Lab Session on Hashing
- Sorting 1: Count Sort & Merge Sort
- Sorting 2: Quick Sort & Comparator Problems
- Sample Contest: Dual Camera Proctoring
- Contest 1: Arrays, Bit Manipulation, Recursion, Math, Hashing & Sorting
Advanced DSA: Linear & Non-Linear Structures
- Searching 1: Binary Search on Array
- Searching 2: Binary Search on Answer
- Lab Session on Searching
- Classes, Objects & Linked List Introduction
- Linked List: Basic Problems
- Stacks
- Lab Session on Stacks
- Queues: Implementation & Problems
- Trees 1: Structure & Traversal
- Trees 2: BST
- Lab Session on Binary Trees
- Revision of DSA 1 & 2
- Break
- Contest 2 : Searching, Linked List, Stacks, Queues , Trees & contest discussion
Advanced DSA: Backtracking & Advanced Trees
- Maths: Combinatorics Basics & Prime Numbers
- Lab Session on Prime Numbers & 2 Pointers
- Lab Session on Maths & 2 Pointers
- Backtracking
- Lab Session on Backtracking
- Linked List: Sorting and Problems
- Linked List: Doubly Linked List & Detecting Loop
- Trees 4: Morris Inorder Traversal + LCA
- Lab Session on Binary Trees 2
- Hashing 3: Internal Implementation & Problems
- Contest 3: Math, Two Pointers, Backtracking, Linked List , Trees & contest discussion
Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
- Heaps: Introduction
- Heap Sort & Greedy
- Lab Session on Heaps & Greedy
- Lab Session on Interview Problems 1
- DP 1: One Dimensional
- DP 2: Two Dimensional
- DP 3: Knapsack
- Lab Session on Applications of Knapsack
- Graphs 1: Introduction, DFS & Cycle Detection
- Graphs 2: BFS & MST
- Graphs 3: Dijkstra Algo & Topological Sort
- Lab Session on Interview Problems 2
- Revision of DSA 3 & 4
- Contest 4: Heaps, Greedy, DP & Graphs
- Mandatory Skill Evaluation Test: DSA
- Skill Evaluation Test Discussion + How to ace DSA Interview
- DSA : Real World Project 1 (Social Network Analyzer)
- DSA : Real world Project 2 ( Invoice Merger )
Databases & SQL
Databases & SQL
- Introduction to DBMS & Keys
- CRUD Operations - 1
- CRUD Operations - 2
- Joins
- Aggregate Queries
- Joins and Aggregate Queries Working Session
- Subqueries & Views
- Indexing
- Transactions
- Window Functions
- Schema Design - 1
- Schema Design - 2
- SQL and Schema Design
Backend
Foundations of Object-Oriented Design & Scalable Systems
- Intro to LLD for Scalable & AI-Ready Systems
- OOP-1: Intro to OOP Lab
- OOP-2: Access Modifiers and Constructors
- OOP-3: Inheritance and Polymorphism
- OOP-4: Interfaces, Abstract Classes
- Concurrency-1: Introduction to Processes and Threads
- Concurrency-2: Executors and Callables
- Concurrency-3: Introduction to Synchronization
- Concurrency-4: Synchronization with Semaphores
- Java Advanced Concepts - 1 [Generics]
- Java Advanced Concepts - 2 [Generics & Collections Lab]
- Java Advanced Concepts - 3 [Streams and Lambdas]
- Java Advanced Concepts - 4 [Exception Handling and Miscellaneous Topics]
- Contest - 1: Java, OOP, and Concurrency
Design Principles & Patterns for Extensible Systems
- SOLID Principles for Extensible Systems with AI integrations
- Design Patterns: Introduction and Singleton
- Design Patterns: Builder
- Design Patterns: Prototype and Registry
- Design Patterns: Leveraging Factory Pattern for Service Abstraction (APIs & AI Services)
- Design Patterns: Adapter and Facade
- Design Patterns: Decorator and Flyweight
- Design Patterns: Behavioural Design Patterns
- UML Diagrams
- Contest - 2: Design Principles & Design Patterns
Applied Design & Machine Coding
- How to Approach Design Problems
- Design TicTacToe
- Code TicTacToe 1
- Code TicTacToe 2
- Design Parking Lot
- Code Parking Lot 1
- Design BookMyShow
- Code BookMyShow 1
- Code BookMyShow 2
- Code BookMyShow 3
- Design Splitwise
- Code Splitwise 1
- Code Splitwise 2
- Low Level Design & Machine Coding
AI-First Backend Capstone Project Primer
- Intro to Backend Systems & AI-Augmented Development
- Version Control and Git
- Learning Git Commands & AI Dev Tools
- Intro to Spring Framework and Building APIs
- MVC, Requests in Spring and Starting First Microservice (with AI Service Integration)
- Calling 3rd Party APIs & LLM/AI Services
- Intro to Spring Data JPA
- JPA Queries and Repositories
- Unit Testing and Good Practices (including AI-assisted testing)
- Authentication vs Authorization, OAuth2, JWT
- Implementing UserAuthService
- Deploying Backend & AI-Enabled Applications to AWS
AI-First Backend Capstone Project Advance
- RestTemplate, Resilience & Handling Failures in AI/API Systems
- UUIDs and Representing Inheritance
- Mocking and Writing Unit Tests (including AI services)
- Advanced Testing Strategies for Backend Systems
- JWT Generation and Validation
- Authentication - Implementing OAuth 2
- EBS, RDS
- VPC, Security Groups, Route 53
- Implementing Search: Paging, Sorting & Intro to Semantic Search
- Creating Payment Microservice
- Implementing Stripe PG and Reconciliation
- Optimizing APIs using Redis and Kafka for Async & AI Workloads
- Spring Cloud for Distributed Microservices & AI Services
- Spring Cloud: API Gateway, Load Balancing, Logging & Monitoring
- Docker for Backend & AI Service Deployment
ElectiveBuild a Production-Ready AI-Enabled System
- Module Introduction - Intro to LLMs for Backend Engineers & Prompt
- Engineering for Backend APIs
- Building BookMyShow Chat Agent - 1
- Building BookMyShow Chat Agent - 2
- Building BookMyShow Chat Agent - 3
- Buildng Splitwise AI Receipt Processor - 1
- Buildng Splitwise AI Receipt Processor - 2
- Buildng Splitwise AI Receipt Processor - 3
- Backend Capstone Project: Contest
Fullstack
Web Platform Foundations & UI Systems
- How the Web Works: Browsers, HTML, Developer Tools, and AI Inspection
- Semantic HTML, Forms, and Structured User Input
- CSS Foundations: Cascade, Selectors, Box Model, and Units
- Layout Systems I: Display, Positioning, and Flexbox
- Layout Systems II: Responsive Design, Media Queries, and Grid
- CSS Variables, Transitions, and Visual Polish
- UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
- From Design to Code: AI-Assisted UI Build, Review, and Refinement
- HTML & CSS Certification Contest
JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
- Full Stack LLD: JS-1: JS Refresher and Code Execution
- Full Stack LLD: JS-2: OOPS-1 : This, Bind, Call, Apply, Inheritance
- Full Stack LLD: JS-3: Polyfills of call,bind ,apply & deep copy-shallow copy
- "Full Stack LLD: JS-4: Array , HOFs and it's Polyfills"
- Full Stack LLD: JS-5: ES6 Classes and Objects
- Full Stack LLD: JS-6: Closure and It's application
- Full Stack LLD: JS-7: OOPS-2 : Object creation, Freezing objects
- Full Stack LLD: JS-8: Event loop and Callback
- Full Stack LLD: JS-9: Promises and MicroTask Queue
- Full Stack LLD: JS-10: Promise chaining and Imp polyfills
- Full Stack LLD: JS-11: Async await & Error handling
- Full Stack LLD: JS-12: ES6 DataTypes and Modules
- Full Stack LLD: FE Machine coding-1:Intro to the DOM
- Full Stack LLD: FE Machine coding-2: Events & Event Handling, Bubbling & capturing
- Full Stack LLD & Projects Certification Contest - JavaScript
React and Frontend Product Architecture Fundamentals
- React Foundations: Components, JSX and Thinking in UI Trees
- React Tooling and TypeScript Setup: Build Tools, JSX, TS Basics and Project Structure
- Props, Lists, Forms and Typed Component Composition
- State, Events and Interactive UI in React
- Lifting State Up, useEffect and Data Flow in Component Trees
- Product Lab 1: IMDB App: App Setup, Routing and Frontend Structure
- Product Lab 2: IMDB App: Movies Page, Pagination and Data Rendering
- Product Lab 3: IMDB App : API Integration, Watchlist and Local Storage
- Product Lab 4: IMDB App : Search, Sorting, Filtering and Shared State
- Context API, State Sharing and Component Communication
- Redux Foundations: Store Design, Actions and Predictable State
- Redux Integration Lab: Product Scale State Management in React
- React Certification Contest
Backend Product Systems, APIs and Production Engineering
- Backend Foundations: Node.js, APIs, Express and Service Thinking
- Data Systems: MongoDB, Mongoose, Schema Design and SQL vs NoSQL Thinking
- Middleware, Validation and MVC for Scalable Backend Structure
- Product Lab 1: Backend Architecture, Domain Modeling and Project Setup
- Product Lab 2: Authentication, Authorization and Role Based Access
- Product Lab 3: Protected Routes, Tokens and Session Aware Flows
- Product Lab 4: Movies, Theatres and Show APIs
- Product Lab 5: Partner Workflows, Admin Approval and Moderated Actions
- Product Lab 6: Booking Flow, Seat Management and Transaction Safety
- Product Lab 7: Payments, Ticket Generation and Order Lifecycle
- Product Lab 8: Email Workflows, Password Reset and User Communication
- Realtime Backend Systems: WebSockets, Live Updates and Event Driven Flows
Backend Product Systems - Deep Dive
- Backend Quality Lab: API Testing, Debugging and Error Handling
- Backend Security Lab: Validation, Auth Hardening, Abuse Prevention and Safe Defaults
- Production Readiness: Environment Management, Deployment, Logging and Docker Basics
- Scalability Lab: Caching, Queues, Background Jobs and Data Flow Trade Offs
- AI Feature Integration Lab: LLM APIs, Structured Responses and Backend Orchestration
- Architecture and Interview Lab: Backend Design, Trade Offs and AI Assisted Review
- MERN Certification Contest
ElectiveFoundations of AI-Assisted Full-Stack Development
- Full-Stack Development in the Age of AI
- AI Coding Tools for Full-Stack Builders
- Prompting for UI, Logic, APIs, and Debugging
- Reviewing and Validating AI-Generated Full-Stack Code
- From Screen to Server: AI-Assisted Development Workflows
- Building Faster Without Losing Fundamentals
ElectiveFrontend Systems & Machine Coding Mastery
- Full Stack LLD: FE Machine coding: Case Studies
- Full Stack LLD: FE Machine coding: Browser Perf & Memory leaks
- Full Stack LLD: FE Machine coding: HTTP and network Optimization
- Full Stack LLD: FE Machine coding:- Typeahead[Intersection Obs, Debouncing, Throttling]
- Full Stack LLD: FE Machine coding: - Kanban board-1
- Full Stack LLD: FE Machine coding: Kanban board-2
- Full Stack LLD & Projects: Contest - FE Machine Coding
Elective React, TypeScript and Frontend Product Architecture Deep Dive
- TypeScript Foundations for JavaScript Developers
- Advanced Hooks: useRef, useMemo, useCallback and useReducer
- Custom Hooks and Reusable Logic Patterns
- React Performance Lab: Rendering, Memoization and UI Efficiency
- Machine Coding Lab: Component Design, State Design and Real UI Problem Solving
- Architecture Studio: React Patterns, State Trade Offs and AI Assisted Review
- Next.js Foundations: App Router, Layouts and Modern React Delivery
- Next.js Data Fetching: Server and Client Components, Rendering Strategy and SEO
- Next.js Product Lab: Forms, Route Handlers, Auth Flow and Deployment
- Advanced React Systems: Fiber, Concurrent Rendering, Suspense, Lazy Loading and Error Boundaries
- React Interview and Frontend Reasoning Lab
Forward Deployed Engineer (FDE)
FDE Foundations: Python, Workflow & Delivery
- The FDE Role: Customer-Embedded Engineering
- Problem Discovery & Solution Thinking for FDEs
- Python Toolchain & Environment Setup (pyenv, uv, ruff, mypy)
- Iterators, Generators & Comprehensions
- Closures, Decorators & Context Managers
- OOP, Concurrency & Async Python
- Pydantic v2, Structured Logging & Profiling
- Git Internals, GitHub Workflows & AI Dev Tools (Cursor, Claude Code, MCP)
- Testing: pytest, Property-Based Testing & CI
- Software Engineering Best Practices (SOLID, Hexagonal Architecture)
- Linux, Shell & Scripting for FDEs
- Assessment: Python Engineering Challenge
Backend Engineering, Observability & Advanced Data Systems
- Introduction to Backend Engineering — HTTP, REST & API Design
- FastAPI: Intro to Deep Dive
- Auth: OAuth2, JWT, OIDC & RBAC
- Building an Order Management Module & its API
- Building Payments & Notifications (Stripe, Celery)
- Building the Demo Frontend
- Real-Time, Queues & Caching (WebSockets, SSE, Redis)
- Observability & Distributed Tracing (OpenTelemetry, Grafana)
- Postgres Advanced: JSONB, Full-Text Search & pgvector
- Postgres Internals: EXPLAIN ANALYZE, Indexing & MVCC
- NoSQL, Document DBs & Vector Databases
- Dimensional Modeling, dbt & Modern Data Stack
- Workflow Orchestration with Airflow & Data Quality
- Event-Driven Architecture & Kafka Fundamentals
- Assessment: Data Pipeline Build & Debug
Full-Stack FDE: TypeScript, React & AI-First Frontends
- TypeScript Fundamentals for Python Engineers
- React Essentials for AI Apps
- Next.js for Full-Stack AI Apps
- Vercel AI SDK & Streaming UIs
- AI Product UX & Customer-Facing Polish
Cloud, DevOps, Kubernetes & Infrastructure
- AWS Core: IAM, VPC & Networking
- Compute, Storage & Managed Services (EC2, S3, RDS, SQS)
- AWS Security & Secrets Management (KMS, Secrets Manager, CloudTrail)
- Docker: Production Containers
- Kubernetes Architecture & Core Concepts
- EKS, Helm & Production Kubernetes
- Kubernetes Networking, Security & GPU Workloads
- CI/CD Pipelines & GitOps (GitHub Actions, ArgoCD)
- Terraform & Infrastructure as Code
- Serverless & Event-Driven Cloud (Lambda, API Gateway, Step Functions)
- SRE & Reliability Engineering for FDEs
- Assessment: Deploy, Break, Fix on Cloud
Enterprise Communication, Consulting & LLM Engineering
- Customer Discovery & Requirements Gathering
- Technical Scoping & Solution Documentation (PRD-lite, options matrix, risk register)
- Stakeholder Communication & Written Artifacts
- Demo Storytelling & Handling Pushback
- LLM Fundamentals for Production
- Prompt Engineering for Production Systems
- RAG Architecture: Ingestion & Retrieval
- RAG over Customer Documents & Hybrid Search
- RAG Evaluation & Iteration (RAGAS)
- LLM Safety, Guardrails & Security
- Cost, Latency & Model Routing
- Assessment: Discovery Call + RAG PoC Build
Agentic Systems & Enterprise Integrations
- Tool Calling, Function Calling & Structured Output
- Agentic Patterns & Production Concerns
- Agent Debugging, Failure Analysis & Evaluation
- MCP & Enterprise Tooling
- Multi-Agent Patterns & Human-in-the-Loop
- Assessment: Agentic System Build & Red-Team
- Enterprise Systems Landscape & Integration Topology
- API Integration Patterns & Connector Design
- Integration Failure Modes & Debugging
- Messy Customer Data & Entity Resolution
- Build: CRM-to-AI Support Copilot
- Assessment: Integration War Room
Application Engineering, Security & Reliability
- Product Thinking & Architecture for FDE Apps
- Frontend Essentials for FDEs: React + TypeScript
- Multi-Tenant Design & Background Workflows (Postgres RLS, Celery)
- Document Processing & AI Extraction Workflows
- Build: Enterprise Document Review App
- Developer Experience & API Documentation
- Enterprise Security for FDE Systems (PII, SOC2, GDPR)
- Secrets, Encryption & Deployment Topologies
- Load Testing, Capacity Planning & Performance (k6)
- Incident Response & Customer-Facing RCA
- Enterprise Readiness Checklist & Go-Live
- Assessment: Secure Deploy + Incident Simulation
System Design, Capstone & Hiring Readiness
- Distributed Systems Fundamentals (CAP, PACELC, Raft, Saga)
- System Design: RAG System at Scale
- System Design: Agentic Platform at Scale
- System Design: Multi-Tenant SaaS Platform
- System Design: Enterprise Integration Hub
- System Design Interview Framework & Practice
- Capstone Sprint 1: Discovery & Solution Design
- Capstone Sprint 2: Core Build & Integration Layer
- Capstone Sprint 3: Harden, Secure & Observe
- Capstone Sprint 4: Red-Team, Eval & Fix
- Capstone Demo Day: Client Panel Presentation
- Interview Readiness & Career Launch
- FDE Mock Engagement: Full Simulation
- Graduation Review: Portfolio Defense & Next Steps
Elective Containerization and Orchestration
- Docker introduction
- Docker image and Docker containers
- Building your own Docker image
- Image and Containers Deep Dive
- Docker volume
- Docker networking deep dive
- Hardening the Docker env. (DevSecOps)
- Demo of implementing industry standard implementation (e.g. in image hardening and other security standards)
- Introduction to Orchestration
- Kubernetes architecture
- Kubernetes Pod deep dive
- Kubernetes Replicaset and Deployment deep dive, side car
- Kubernetes networking
- Scaling options in kubernetes - HPA, CA and VPA - compare with Karpentor
- Introduction to scaling in kubernets, Network policies
- Kubernetes security - RBAC (DevSecOps)
- Kubernetes volumes
Elective AWS : multi-region cloud deep dive
- AWS VPC & Networking Basics
- Advanced AWS Networking
- AWS Observability & CloudWatch
- CloudWatch & CloudTrail Advanced (DevSecOps)
- Docker App on EC2 Project
- AWS Lambda & API Gateway
- End-to-End Project day
- AWS ECS & ECR Intro
- ECS Fundamental
- EKS Basics
- EKS Advanced
- EKS Security & Operations
- Microservices on AWS Project
- Microservices Project – Phase 2
- AWS Security: Identity & Network (DevSecOps)
- AWS Security: Data & Detection (DevSecOps)
- AWS Security Hands-on (DevSecOps)
Elective Storage, Networking & Reliability for FDEs- storage architecture, DR, sharding, CDN, HA, fault tolerance
- Architect the Storage for an Application
- Data Lifecycle Management and Storage Optimization
- Backup and Disaster Recovery Strategies
- Designing the Networking of an Application
- Load Balancing and Auto Scaling Groups
- Designing for scalability of application and data
- Database Sharding Strategies and Hot-Spot Mitigation
- Edge Caching, CDNs, and Latency Reduction
- Microservices Performance — Latency, Throughput, Concurrency
- Designing for High Availability — Multi-Region Active-Active
- Fault Tolerance Engineering — Circuit Breakers, Retries, Backoff
- Graceful Degradation — Rate Limiting, Throttling, Shedding
- Data Consistency Trade-offs — CAP, PACELC
System Design
Distributed System Design & AI-Integrated Architectures
- System Design Foundations & Modern Infrastructure
- Load Balancing, Consistent Hashing & Traffic Routing at Scale
- Caching Systems: CDN, Backend Caches, Cache Invalidation
- Case Study: Caching at Scale (Scaler Code Judge and Contest Leaderboards + AI Workloads)
- Case Study: Caching Facebook News Feed
- CAP / PACELC theorem + Master Slave Replication
- SQL vs NoSQL + Sharding
- Database Orchestration & Shard Creation
- Case study: Google Typeahead (How to approach System Design Problems)
- Case Study: Google Typeahead (Design and Optimizations)
- NoSQL Internals - LSM Tree and Multi Master
- Case Study: Messaging Apps (FB Messenger, Whatsapp, Slack)
- Messaging Queues - Apache Kafka & Zookeeper
- Case Study: ElasticSearch (Full Text Search)
- Case Study: S3, HDFS (Large File Storage)
- Case Study: Uber (Nearest Neighbor Search)
- Case Study: Rate Limiter + Unique ID Generator (Infra)
- Case Study: OTT Platform (OTT)
- Microservices - 1
- Microservices - 2
- Case Study: Ecommerce Platform (Microservices)
Interview Preparation
Mastering LastMile - Interview Simulation
- DSA Interview Simulation: Problem Solving & Thinking Under Pressure
- LLD Interview Simulation: Structuring Scalable Solutions
- HLD Interview Simulation: Designing Systems & Communicating Trad
Data Engineering
Data Engineering
- Introduction to Data Engineering
- Writing Efficient Queries: Part 1
- Writing Efficient Queries: Part 2
- Intro to Hadoop
- HDFS and MAP-REDUCE
- Introduction to Hive
- Advanced features of Hive
- Basics of Spark
- Spark Programming
- Structured API - PySpark
- PySpark Operations
- Introduction to Streaming
- Apache Spark Streaming
- Advanced Spark Streaming
- Additional Streaming Services: Bringing it all together
- Modern Data Architecures
- AWS Services for Data Engineering
- Data Modelling
- Orchestrating data pipelines
- Orchestration Continued
- Distributed Coordination
- Load Balancing
- Data Pillars
- Capstone
Advanced DSA
DSA Edge: Advanced Patterns & Interview Techniques
- DSA Edge : Townhall
- DSA Edge : Townhall (Post-SQL - change name after scheduling)
- Revision of DSA Topics
- Maths: Inverse Mod & Problems
- Backtracking: Famous Problems
- Tries 1: Trie of Character
- Tries 2: Trie of Bits + Problems on Trees
- Strings Pattern Matching
- DP 1: DP on Strings
- DP 2: Famous Problems
- Graphs 1: Bipartite Graph
- Graphs 2: Belleman Ford & Floyd Warshall Algorithm
- Advanced Interview Problems
- DSA Edge Mandatory Contest: Full Syllabus
- DSA Edge Full Syllabus: Contest Discussion
Product Management for Engineers
- Townhall: Product Management
- Introduction to Product Management 1
- Understanding the Product Lifecycle 1
- Understanding the Product Lifecycle 2
- Critical Thinking in Product Development 1
- Critical Thinking in Product Development 2
- Market Structure Analysis and Its Technical Aspects 1
- Market Structure Analysis and Its Technical Aspects 2
- MVPs, Prototyping, and Growth Hacking 1
- MVPs, Prototyping, and Growth Hacking 2
- Concept Development, Validation, and the Role of Developers 1
- Concept Development, Validation, and the Role of Developers 2
- Introduction to Product Analytics 1
Gen AI for Software Engineers
- Introduction to AI Engineering
- Refresher: Modern Text & Image AI Model Architectures
- Getting started with Text Generation LLM APIs (OpenAI API)
- Designing Eval Pipelines for AI Apps and Observability
- Prompt Engineering: Introduction
- Retrieval-Augmented Generation (RAG) Introduction
- Embeddings Deep Dive
- Multimodal & Tabular RAG
- Prompt Engineering: Security
- Agents: Foundations & Planning
- Advanced Agent Concepts
- Agent: Frameworks and Protocols
- Fine Tuning Existing Models
- Audio, Image, Video, Expressions: AI Modalities
- Scaling AI Applications
- Model Quantization Techniques
- Advanced Fine Tuning Techniques
- Dataset Engineering & Inference Optimization