From Fundamentals to Scalability
Full-Stack Programming, System Design &
Gen AI Bootcamp
Transform into an Industry-Ready Software Engineer with AI Tools in 15 Weeks

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Program Overview

CodeReady is a comprehensive 15-week technical training program designed to bridge the employability gap. We transform college students and early-career developers into industry-ready software engineers with practical skills in DSA, System Design, and Gen AI.

🎯 Who Is This For?

  • College students seeking industry-ready skills
  • Recent graduates preparing for tech careers
  • Early-career developers wanting to upskill
  • Anyone motivated to learn programming

πŸ“‹ Prerequisites

  • Basic computer literacy
  • Motivation to learn
  • No prior programming experience required
  • Commitment to 10 hours/week (5 live + 5 practice)

⏱️ Time Commitment

  • 75 hours of live instruction
  • 75 hours of self-paced practice
  • 5 hours per week live sessions
  • 5 hours per week assignments
15 Weeks
75 Live Hours
75 Practice Hours
2 Languages
7 Phases

Learning Phases

7 structured phases taking you from programming fundamentals to scalable system design & Gen AI

Phase Duration Focus Areas
Phase 1: Programming 101 Weeks 1-3 Fundamentals, variables, control flow, loops, functions, OOP, exceptions, file I/O
Phase 2: Data Structures Weeks 4-6 Arrays, linked lists, stacks, queues, trees, graphs, hash tables, recursion
Phase 3: Problem Solving Weeks 7-9 30-40 easy/medium LeetCode-style questions, patterns & guided walkthroughs
Phase 4: Databases Weeks 10-11 MySQL fundamentals, joins, indexes, normalization, transactions; mini-project
Phase 5: System Design Weeks 12-13 Client-server, REST APIs, scalability, caching, load balancers, sharding, diagrams
Phase 6: Gen AI & AI Tools Week 14 Generative AI (ChatGPT, Claude, Gemini), GitHub Copilot, prompt engineering, AI-powered development
Phase 7: Capstone Week 15 2-3 end-to-end mini-apps combining API + DB + frontend concepts with AI enhancement

Technology Stack

Comprehensive tech stack covering the full spectrum of modern software development

πŸ’» Programming Languages

  • Java: Core programming, OOP, collections, data structures
  • Python: Core programming, OOP, data structures, algorithms

🌐 Backend & API Development

  • Python: Flask API framework (RESTful APIs)
  • Java: Spring Boot / Maven-based projects

πŸ—„οΈ Database & Data Persistence

  • MySQL: Relational database management
  • Schema design & normalization
  • SQL queries, joins, indexes, transactions
  • File I/O: JSON, CSV data handling

πŸ§ͺ Testing Frameworks

  • Java: JUnit (unit testing framework)
  • Python: pytest (testing framework)
  • Code coverage tools for both languages

πŸ“¦ Build Tools & Version Control

  • Java: Maven (project management & build tool)
  • Python: pip (package manager)
  • Git: Distributed version control
  • GitHub: Code hosting, pull requests, collaboration

πŸ—οΈ System Design & Architecture

  • REST APIs: API design and implementation
  • HTTP/HTTPS: Web protocols
  • Database Design: Schema design, normalization
  • Caching: CDN, reverse proxy concepts
  • Load Balancing: Concepts and patterns

πŸ€– Gen AI & AI-Powered Development Tools

  • Generative AI: ChatGPT, Claude, Gemini for code generation
  • GitHub Copilot: AI code completion and generation
  • AI-powered debugging and optimization
  • Cursor AI: AI-powered IDE
  • Prompt engineering for software development

πŸ› οΈ Development Tools & IDEs

  • VS Code / Cursor
  • IntelliJ IDEA (for Java development)
  • PyCharm (for Python development)
  • Terminal: Bash/Shell scripting

Learning Outcomes

By completing CodeReady, you'll demonstrate job-ready competence in dual-language programming, data structures & algorithms, database design, API development, and scalable systems.

1️⃣ Dual-Language Proficiency

Write robust code in Java and Python with idiomatic patterns

2️⃣ Data Structures & Algorithms

Implement arrays, trees, graphs, heaps and analyze complexity

3️⃣ Problem-Solving Patterns

Two pointers, sliding window, recursion, DP, graph algorithms

4️⃣ Database Design & SQL

Normalized schemas, joins, indexing, transactions & isolation

5️⃣ RESTful API Development

HTTP methods, stateless design, caching, pagination, auth basics

6️⃣ Scalable Architecture

Load balancing, sharding, CAP, trade-off analysis & diagrams

7️⃣ End-to-End Delivery

Integrate backend + DB + a simple frontend; write clean docs

8️⃣ Interview Readiness

Explain decisions, walk through DSA, and whiteboard designs

9️⃣ Gen AI & AI-Powered Development

Master Generative AI tools (ChatGPT, Claude, Gemini), GitHub Copilot, and AI-powered workflows for modern software development

Weekly Curriculum

15 weeks of structured learning with daily topics, assignments, and quizzes

Weeks 1-3: Programming 101 (Phase 1)

Week 1

  • Day 1: Variables, types, operators
  • Day 2: Control flow & boolean logic
  • Day 3: Loops & iteration patterns
  • Day 4: Functions/methods, scope & returns
  • Day 5: I/O & core collections (list/array/dict)
Assignment: CLI calculator (both languages). Quiz: 10 MCQs + 1 coding.

Week 2

  • Day 1: OOP basics (classes/objects)
  • Day 2: Encapsulation, inheritance, polymorphism
  • Day 3: Exceptions & error handling
  • Day 4: File I/O in Java & Python
  • Day 5: OOP workshop (build a mini library)
Assignment: Book Library class with save/load. Quiz: 10 MCQs + 1 coding.

Week 3

  • Day 1: Modular programming & packaging
  • Day 2: Complexity & Big-O
  • Day 3: Debugging & unit testing (JUnit/pytest)
  • Day 4: Git/GitHub basics; PR etiquette
  • Day 5: Mini-project: CLI To-Do app (CRUD)
Assignment: To-Do app with tests & README. Quiz: 10 MCQs + 1 coding.

Weeks 4-6: Data Structures (Phase 2)

Week 4

  • Day 1: Arrays & lists
  • Day 2: Linked lists (SLL/DLL)
  • Day 3: Stacks (LIFO) & use-cases
  • Day 4: Queues/Deque & variants
  • Day 5: Lab: implement DS in both languages
Assignment: Implement List/Stack/Queue APIs. Quiz: 10 MCQs + 1 coding.

Week 5

  • Day 1: Trees & recursion basics
  • Day 2: BST ops (insert/delete/search)
  • Day 3: Graphs & adjacency models
  • Day 4: Traversals: DFS/BFS
  • Day 5: Workshop: paths, levels, cycles
Assignment: BST + BFS on grid; README with Big-O. Quiz: 10 MCQs + 1 coding.

Week 6

  • Day 1: Hash tables (hashing, collisions)
  • Day 2: Heaps/PQs; heap sort
  • Day 3: Recursion deep-dive
  • Day 4: Memory mgmt, GC concepts
  • Day 5: DS practice set (mixed)
Assignment: LRU Cache (hashmap+DLL). Quiz: 10 MCQs + 1 coding.

Weeks 7-9: Problem Solving (Phase 3)

Focus on patterns and 30-40 easy/medium LeetCode-style questions with guided walkthroughs. Daily flow: short lecture goals β†’ key takeaways β†’ real-world analogy β†’ hands-on exercise β†’ stretch β†’ review.

Week 7

  • Day 1: Problem analysis & constraints; pattern library intro
  • Day 2: Two-pointers; sorted arrays & string scans
  • Day 3: Sliding window (fixed & variable)
  • Day 4: Sorting fundamentals; stability & when to use what
  • Day 5: Review set (6-8 questions) + live walkthrough
Assignment: 10 questions (2Γ— two-pointers, 4Γ— sliding-window, 4Γ— sorting). Quiz: 10 MCQs + 1 coding.

Week 8

  • Day 1: Recursion patterns & backtracking (subsets, permutations)
  • Day 2: Dynamic Programming I (memoization vs tabulation)
  • Day 3: DP II (knapsack, coin change, LIS ideas)
  • Day 4: Graph algorithms I (BFS shortest path, topo sort)
  • Day 5: Mock interview #1 (15-min DSA + 10-min feedback per student)
Assignment: 10 questions (3Γ— recursion/backtracking, 5Γ— DP, 2Γ— graph BFS). Quiz: 10 MCQs + 1 coding.

Week 9

  • Day 1: Greedy techniques; exchange arguments & proofs of correctness (informal)
  • Day 2: Advanced graphs (Dijkstra intro; when BFS vs Dijkstra)
  • Day 3: Mixed set (hashing, heap, prefix sum)
  • Day 4: System-aware problem solving (I/O limits, memory caps)
  • Day 5: Mock interview #2 + feedback & personalized plan
Assignment: 10 questions (2Γ— greedy, 3Γ— heap, 3Γ— hashing/prefix, 2Γ— graph). Quiz: 10 MCQs + 1 coding.

Weeks 10-11: Databases (Phase 4)

Week 10

  • Day 1: Relational model, tables, PK/FK; ER β†’ schema
  • Day 2: Normalization (1NF-3NF); denormalization trade-offs
  • Day 3: SELECT, WHERE, ORDER BY, LIMIT; CRUD basics
  • Day 4: Joins (INNER/LEFT/RIGHT/FULL), GROUP BY, HAVING
  • Day 5: Lab: design a Course–Student–Enrollment schema
Assignment: Create schema & seed data; 12 queries (mix of joins & groups). Quiz: 12 MCQs + 1 query.

Week 11

  • Day 1: Indexes & query plans; when indexes hurt/help
  • Day 2: Transactions, ACID; isolation levels & anomalies
  • Day 3: Stored routines & views (intro), pagination patterns
  • Day 4: NoSQL overview (key-value, document); when to choose which
  • Day 5: Mini-project: Analytics queries & simple dashboard export (CSV/JSON)
Assignment: Optimize queries (add/remove indexes), measure timings, document rationale. Quiz: 12 MCQs + 1 query.

Weeks 12-13: System Design (Phase 5)

Week 12

  • Day 1: Client-server, REST, HTTP verbs, idempotency; API design (resources, pagination)
  • Day 2: Statelessness, session vs token auth (concepts); rate limiting basics
  • Day 3: Caching (CDN, reverse proxy, app-level); cache invalidation strategies
  • Day 4: Load balancing (round-robin, least-conn); health checks; blue/green overview
  • Day 5: Design exercise: URL Shortener (read-heavy, cache, DB schema, API)
Assignment: Write a 2-page design doc + simple API spec (OpenAPI snippet encouraged). Quiz: 12 MCQs.

Week 13

  • Day 1: Databases at scale: replication vs sharding; read/write paths
  • Day 2: Consistency models; CAP & PACELC intuition; queues for decoupling
  • Day 3: Observability 101 (logs, metrics, traces) & SLOs; error budgets
  • Day 4: Design exercise: News Feed/Timeline (fan-out, denorm, caches)
  • Day 5: Mock system design interview + structured feedback rubric
Assignment: 3-page design doc with diagram and capacity estimates (QPS, storage). Quiz: 12 MCQs.

Week 14: Gen AI & AI Tools (Phase 6)

Week 14

  • Day 1: GitHub Copilot fundamentals: Installation, configuration, code generation
  • Day 2: ChatGPT for development: Prompt engineering, debugging, documentation
  • Day 3: Claude & advanced AI: Code analysis, architecture suggestions, optimization
  • Day 4: AI debugging tools: Error analysis, security scanning, performance optimization
  • Day 5: Modern AI workflow: CI/CD integration, AI ethics & best practices
Assignment: Enhance capstone project using AI tools. Quiz: 10 MCQs on AI tool usage.

Week 15: Capstone Project (Phase 7)

Build 2-3 complete end-to-end applications that combine API + Database + Frontend concepts with AI enhancement. Teams of 2-3; PR-based workflow on GitHub.

  • Project 1: Smart To-Do with Analytics (REST API, MySQL, dashboard)
  • Project 2: E-Commerce Lite (Catalog, cart, orders, inventory consistency)
  • Project 3: Minimal Chat Service (User/channel models, message APIs, pagination)
Deliverables: Design doc (3-5 pages), API spec (OpenAPI), DB schema (ER + DDL), runnable code, README, demo video (≀5 min).

Capstone Projects

Build 2-3 complete end-to-end applications that combine API + Database + Frontend concepts

πŸ“ Smart To-Do with Analytics

  • REST API (CRUD tasks, labels)
  • MySQL schema (users, tasks, events)
  • Basic dashboard (completed/overdue)
  • Pagination, search functionality
  • Caching layer for popular queries

πŸ›’ E-Commerce Lite

  • Catalog, cart, orders management
  • Inventory consistency
  • Simple checkout flow
  • Eventual consistency vs transactions
  • Rate limiting on checkout

πŸ’¬ Minimal Chat Service

  • User/channel models
  • Message send/fetch APIs
  • Pagination for messages
  • Cache for recent messages
  • Long-polling vs polling trade-offs

πŸ“‹ Project Requirements

  • Design Document: 3-5 pages with trade-offs & capacity estimates
  • API Specification: OpenAPI/Swagger documentation
  • Database Schema: ER diagrams + DDL scripts
  • Implementation: Runnable code with seed data
  • Documentation: README with setup instructions
  • Demo Video: ≀5 minutes walking through endpoints

Evaluation Rubric

Transparent and fair grading system focused on practical skills

40% Assignments

Code correctness, tests, readability, docs, PR quality

20% Quizzes

Concept mastery via MCQs + short coding/SQL

40% Projects

Design docs, implementation, demo, teamwork & reviews

πŸ“Š Detailed Rubric (Per PR/Assignment)

  • Correctness (40%) – Passes tests; handles edges
  • Design (20%) – Cohesive APIs, clean abstractions, data modeling
  • Code Quality (20%) – Readability, naming, structure, comments
  • Testing (10%) – Unit tests (JUnit/pytest), coverage on core logic
  • Documentation (10%) – README, usage, trade-offs, diagrams

⚠️ The Job Market Harsh Reality

India produces 1.5 million engineers yearly, but only 10% secure jobs. 83% fail to find relevant employment due to the severe mismatch between college curricula and industry needs. Traditional education focuses on theory, but employers demand practical skills in Data Structures, Algorithms, System Design, and Gen AI.

1.5M Engineers Graduated Yearly
10% Get Jobs
83% Unemployed

Ready to Transform Your Tech Career?

Join our free webinar to learn more about the CodeReady bootcamp and how we can help you become industry-ready.

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