Curriculum
OUTLINE

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 Beginners18 Months

Segment Module
Type		 Module name Duration (months)
Programming Fundamentals Core Programming Language Fundamentals - Thinking with AI: Logics, Loops & Control Flow 1
Core Programming Language Fundamentals - 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 4
Core Advanced DSA: Linear & Non-Linear Structures
Core Advanced DSA: Backtracking & Advanced Trees
Core Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
Optional DSA Edge: Advanced Patterns & Interview Techniques 1
Databases & SQL Core Databases & SQL 1
Backend Specialisation Foundations of Object-Oriented Design & Scalable Systems 4
Specialisation Design Principles & Patterns for Extensible Systems
Specialisation Applied Design & Machine Coding
Specialisation AI-First Backend Capstone Project 1.5
Specialisation Build a Production-Ready AI-Enabled System
Fullstack Specialisation Foundations of AI-Assisted Full-Stack Development 6
Specialisation Web Platform Foundations & UI Systems
Specialisation JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
Specialisation React, TypeScript and Frontend Product Architecture
Specialisation Backend Product Systems, APIs and Production Engineering
System Design Core Distributed System Design & AI-Integrated Architectures 1.5
Interview Preparation Elective Mastering LastMile - Interview Simulation 1.5 weeks
Forward Deployment Engineering Elective Forward Deployment Engineering (FDE) Lab 2.5
Elective Data Engineering 2
Elective Product Management for Engineers 1
Elective Gen AI for Software Engineers 1

* 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 Intermediate18 Months

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 4
Core Advanced DSA: Linear & Non-Linear Structures
Core Advanced DSA: Backtracking & Advanced Trees
Core Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
Optional DSA Edge: Advanced Patterns & Interview Techniques 1
Databases & SQL Core Databases & SQL 1
Backend: LLD Specialisation Foundations of Object-Oriented Design & Scalable Systems 4
Specialisation Design Principles & Patterns for Extensible Systems
Specialisation Applied Design & Machine Coding
Fullstack Specialisation Foundations of AI-Assisted Full-Stack Development 6
Specialisation Web Platform Foundations & UI Systems
Specialisation JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
Specialisation React, TypeScript and Frontend Product Architecture
Specialisation Backend Product Systems, APIs and Production Engineering
System Design Core Distributed System Design & AI-Integrated Architectures 1.5
Backend Specialisation AI-First Backend Capstone Project 1.5
Specialisation Build a Production-Ready AI-Enabled System
Interview Preparation Elective Mastering LastMile - Interview Simulation 1.5 weeks
Forward Deployment Engineering Elective Forward Deployment Engineering (FDE) Lab 2.5
Elective Data Engineering 2
Elective Product Management for Engineers 1
Elective Gen AI for Software Engineers 2

* 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 Advanced18 Months

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 4
Core Advanced DSA: Linear & Non-Linear Structures
Core Advanced DSA: Backtracking & Advanced Trees
Core Advanced DSA: DP, Heaps & Graphs — Crack It with AI Edge
Optional DSA Edge: Advanced Patterns & Interview Techniques 1
SQL Core SQL 1
Backend: LLD Specialisation Foundations of Object-Oriented Design & Scalable Systems 4
Specialisation Design Principles & Patterns for Extensible Systems
Specialisation Applied Design & Machine Coding
Fullstack Specialisation Foundations of AI-Assisted Full-Stack Development 6
Specialisation Web Platform Foundations & UI Systems
Specialisation JavaScript Runtime Systems, Browser APIs & Product Engineering Labs
Specialisation React, TypeScript and Frontend Product Architecture
Specialisation Backend Product Systems, APIs and Production Engineering
System Design Core Distributed System Design & AI-Integrated Architectures 1.5
Backend Specialisation AI-First Backend Capstone Project 1.5
Specialisation Build a Production-Ready AI-Enabled System
Interview Preparation Elective Mastering LastMile - Interview Simulation 1.5 weeks
Forward Deployment Engineering Elective Forward Deployment Engineering (FDE) Lab 2.5
Data Engineering Elective Data Engineering 2
Product Management Elective Product Management for Engineers 1
Gen AI for Software Engineers Elective Gen AI for Software Engineers 2

* 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 Beginners18 Months

Programming Fundamentals

Programming Language 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

Programming Language Fundamentals - 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
  • MindStudio: Building AI Apps Visually

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 )

Optional DSA Edge: Advanced Patterns & Interview Techniques

  • DSA 4.2 : Townhall
  • DSA 4.2 : 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 4.2 Mandatory Contest: Full Syllabus
  • DSA 4.2 Full Syllabus: Contest Discussion

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
  • Splitwise 1
  • Splitwise 2
  • Machine Coding
  • Break

AI-First Backend Capstone Project

  • 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
  • RestTemplate, Resilience & Handling Failures in AI/API Systems
  • Intro to Spring Data JPA
  • UUIDs and Representing Inheritance
  • JPA Queries and Repositories
  • Unit Testing and Good Practices (including AI-assisted testing)
  • Mocking and Writing Unit Tests (including AI services)
  • Advanced Testing Strategies for Backend Systems
  • Authentication vs Authorization, OAuth2, JWT
  • Implementing UserAuthService
  • JWT Generation and Validation
  • Authentication - Implementing OAuth 2
  • Deploying Backend & AI-Enabled Applications to AWS
  • 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

Build a Production-Ready AI-Enabled System

  • Intro to LLMs for Backend Engineers
  • Prompt Engineering for Backend APIs
  • Designing AI Features (Chat, Search, Recommendations)
  • Backend Capstone Project: Contest

Fullstack

Foundations 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

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
  • UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
  • From Design to Interface: AI-Assisted Responsive UI Build
  • AI for UI Building: Design-to-Code, Review, and Refinement

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
  • 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
  • TypeScript Foundations for JavaScript Developers

React, TypeScript and Frontend Product Architecture

  • 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
  • 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

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 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

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

Forward Deployment Engineering

Forward Deployment Engineering (FDE) Lab

Data Engineering

  • Introduction to Data Engineering
  • SQL - 01
  • SQL - 02
  • SQL - 03
  • SQL - 04
  • SQL - 05: Window functions
  • Writing Optimised Queries - Nested and Repeated Data
  • Optimised Queries - Indexes and Partitioning
  • SQL Interview Prep Session
  • Hadoop Ecosystem Fundamentals of Distributed Systems
  • Hadoop Ecosystem Fundamentals of Distributed Systems continued
  • Map Reduce Framework
  • Data Modeling
  • Data Warehousing with Apache Hive
  • Data Warehousing with Apache Hive Cont
  • Cloud offerings for Data Warehouses - AWS Redshift
  • Data Lakes
  • Data Processing with Spark: Dataframe -1
  • Data Processing with Spark: Dataframe -2
  • Orchestrating the ETL pipeline using Apache Airflow
  • Building a stream monitoring Dashboard - 1
  • Building a stream monitoring Dashboard - 2
  • Maang Data Engineering Interview Preparation
  • Case Studies - Introduction

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 and ML
  • Introduction to Deep Learning
  • GenAI, LLMs
  • Transformer Architecture
  • Embeddings and RAG
  • LLM Evaluations
  • AI Agents
  • Building Production-Ready AI Applications

Intermediate 18 Months

Programming Fundamentals

Intermediate DSA with AI Assistance

  • Intermediate DSA: Time Complexity
  • Intermediate DSA: Introduction to Arrays & Basics of AI
  • Intermediate DSA: Lab Session on TC, SC, Output & Debugging
  • Intermediate DSA: Arrays: Prefix Sum & Carry Forward with AI-Assisted Problem Solving
  • Intermediate DSA: Lab Session on Prefix Sum & Carry Forward
  • Intermediate DSA: Arrays: Arrays techniques & smart prompting
  • Intermediate DSA: Lab Session on Memory Management & Sorting Basics
  • Intermediate DSA: Bit Manipulations Basics
  • Intermediate DSA: Lab Session on 2D Matrices
  • Intermediate DSA : Strings & Immutability visualisations through AI
  • Intermediate DSA: Lab on Matrix & Strings using AI
  • Intermediate DSA: 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
  • MindStudio: Building AI Apps Visually

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 )

Optional DSA Edge: Advanced Patterns & Interview Techniques

  • DSA 4.2 : Townhall
  • DSA 4.2 : 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 4.2 Mandatory Contest: Full Syllabus
  • DSA 4.2 Full Syllabus: Contest Discussion

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 LLD

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
  • Break

Fullstack

Foundations 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

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
  • UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
  • From Design to Interface: AI-Assisted Responsive UI Build
  • AI for UI Building: Design-to-Code, Review, and Refinement

JavaScript Runtime Systems, Browser APIs & Product Engineering Labs

  • JS Refresher and Code Execution
  • OOPS-1 : This, Bind, Call, Apply, Inheritance
  • Polyfills of call,bind ,apply & deep copy-shallow copy
  • Array , HOFs and it's Polyfills
  • ES6 Classes and Objects
  • Closure and It's application
  • OOPS-2 : Object creation, Freezing objects
  • Event loop and Callback
  • Promises and MicroTask Queue
  • Promise chaining and Imp polyfills
  • Async await & Error handling
  • ES6 DataTypes and Modules
  • Contest - JavaScript
  • FE Machine coding-1:Intro to the DOM
  • FE Machine coding-2: Events & Event Handling, Bubbling & capturing
  • FE Machine coding-3: Machine coding case studies
  • FE Machine coding-4: Browser Perf & Memory leaks
  • FE Machine coding-5: HTTP and network Optimization
  • FE Machine coding-6:- Typeahead[Intersection Obs, Debouncing, Throttling]
  • FE Machine coding-7: - Kanban board-1
  • FE Machine coding-8: Kanban board-2
  • Contest - Machine Coding
  • TypeScript Foundations for JavaScript Developers

React, TypeScript and Frontend Product Architecture

  • 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
  • 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

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 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

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)

Backend

AI-First Backend Capstone Project

  • 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
  • RestTemplate, Resilience & Handling Failures in AI/API Systems
  • Intro to Spring Data JPA
  • UUIDs and Representing Inheritance
  • JPA Queries and Repositories
  • Unit Testing and Good Practices (including AI-assisted testing)
  • Mocking and Writing Unit Tests (including AI services)
  • Advanced Testing Strategies for Backend Systems
  • Authentication vs Authorization, OAuth2, JWT
  • Implementing UserAuthService
  • JWT Generation and Validation
  • Authentication - Implementing OAuth 2
  • Deploying Backend & AI-Enabled Applications to AWS
  • 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

Build a Production-Ready AI-Enabled System

  • Intro to LLMs for Backend Engineers
  • Prompt Engineering for Backend APIs
  • Designing AI Features (Chat, Search, Recommendations)
  • Backend Capstone Project: Contest
  • Break

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

Forward Deployment Engineering

Forward Deployment Engineering (FDE) Lab

Data Engineering

  • Introduction to Data Engineering
  • SQL - 01
  • SQL - 02
  • SQL - 03
  • SQL - 04
  • SQL - 05: Window functions
  • Writing Optimised Queries - Nested and Repeated Data
  • Optimised Queries - Indexes and Partitioning
  • SQL Interview Prep Session
  • Hadoop Ecosystem Fundamentals of Distributed Systems
  • Hadoop Ecosystem Fundamentals of Distributed Systems continued
  • Map Reduce Framework
  • Data Modeling
  • Data Warehousing with Apache Hive
  • Data Warehousing with Apache Hive Cont
  • Cloud offerings for Data Warehouses - AWS Redshift
  • Data Lakes
  • Data Processing with Spark: Dataframe -1
  • Data Processing with Spark: Dataframe -2
  • Orchestrating the ETL pipeline using Apache Airflow
  • Building a stream monitoring Dashboard - 1
  • Building a stream monitoring Dashboard - 2
  • Maang Data Engineering Interview Preparation
  • Case Studies - Introduction

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 and ML
  • Introduction to Deep Learning
  • GenAI, LLMs
  • Transformer Architecture
  • Embeddings and RAG
  • LLM Evaluations
  • AI Agents
  • Building Production-Ready AI Applications

Advanced18 Months

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
  • MindStudio: Building AI Apps Visually

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 )

Optional DSA Edge: Advanced Patterns & Interview Techniques

  • DSA 4.2 : Townhall
  • DSA 4.2 : 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 4.2 Mandatory Contest: Full Syllabus
  • DSA 4.2 Full Syllabus: Contest Discussion

SQL

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 LLD

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
  • Break

Fullstack

Foundations 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

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
  • UI Debugging: Specificity, Inheritance, Stacking, DevTools, and AI Review
  • From Design to Interface: AI-Assisted Responsive UI Build
  • AI for UI Building: Design-to-Code, Review, and Refinement

JavaScript Runtime Systems, Browser APIs & Product Engineering Labs

  • JS Refresher and Code Execution
  • OOPS-1 : This, Bind, Call, Apply, Inheritance
  • Polyfills of call,bind ,apply & deep copy-shallow copy
  • Array , HOFs and it's Polyfills
  • ES6 Classes and Objects
  • Closure and It's application
  • OOPS-2 : Object creation, Freezing objects
  • Event loop and Callback
  • Promises and MicroTask Queue
  • Promise chaining and Imp polyfills
  • Async await & Error handling
  • ES6 DataTypes and Modules
  • Contest - JavaScript
  • FE Machine coding-1:Intro to the DOM
  • FE Machine coding-2: Events & Event Handling, Bubbling & capturing
  • FE Machine coding-3: Machine coding case studies
  • FE Machine coding-4: Browser Perf & Memory leaks
  • FE Machine coding-5: HTTP and network Optimization
  • FE Machine coding-6:- Typeahead[Intersection Obs, Debouncing, Throttling]
  • FE Machine coding-7: - Kanban board-1
  • FE Machine coding-8: Kanban board-2
  • Contest - Machine Coding
  • TypeScript Foundations for JavaScript Developers

React, TypeScript and Frontend Product Architecture

  • 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
  • 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

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 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

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)

Backend

AI-First Backend Capstone Project

  • 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
  • RestTemplate, Resilience & Handling Failures in AI/API Systems
  • Intro to Spring Data JPA
  • UUIDs and Representing Inheritance
  • JPA Queries and Repositories
  • Unit Testing and Good Practices (including AI-assisted testing)
  • Mocking and Writing Unit Tests (including AI services)
  • Advanced Testing Strategies for Backend Systems
  • Authentication vs Authorization, OAuth2, JWT
  • Implementing UserAuthService
  • JWT Generation and Validation
  • Authentication - Implementing OAuth 2
  • Deploying Backend & AI-Enabled Applications to AWS
  • 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

Build a Production-Ready AI-Enabled System

  • Intro to LLMs for Backend Engineers
  • Prompt Engineering for Backend APIs
  • Designing AI Features (Chat, Search, Recommendations)
  • Backend Capstone Project: Contest
  • Break

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

Forward Deployment Engineering

Forward Deployment Engineering (FDE) Lab

Data Engineering

Data Engineering

  • Introduction to Data Engineering
  • SQL - 01
  • SQL - 02
  • SQL - 03
  • SQL - 04
  • SQL - 05: Window functions
  • Writing Optimised Queries - Nested and Repeated Data
  • Optimised Queries - Indexes and Partitioning
  • SQL Interview Prep Session
  • Hadoop Ecosystem Fundamentals of Distributed Systems
  • Hadoop Ecosystem Fundamentals of Distributed Systems continued
  • Map Reduce Framework
  • Data Modeling
  • Data Warehousing with Apache Hive
  • Data Warehousing with Apache Hive Cont
  • Cloud offerings for Data Warehouses - AWS Redshift
  • Data Lakes
  • Data Processing with Spark: Dataframe -1
  • Data Processing with Spark: Dataframe -2
  • Orchestrating the ETL pipeline using Apache Airflow
  • Building a stream monitoring Dashboard - 1
  • Building a stream monitoring Dashboard - 2
  • Maang Data Engineering Interview Preparation
  • Case Studies - Introduction

Product Management

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

Gen AI for Software Engineers

  • Introduction to AI and ML
  • Introduction to Deep Learning
  • GenAI, LLMs
  • Transformer Architecture
  • Embeddings and RAG
  • LLM Evaluations
  • AI Agents
  • Building Production-Ready AI Applications