🎓 Program Overview
Build production-grade full-stack applications across any tech stack — using Claude Code, Cursor IDE, and GitHub Copilot as your development partners from day one. This is not a course about prompting ChatGPT. You will use AI tools the way professional engineering teams use them in 2026: to plan architecture, scaffold projects, write and review code, debug, write tests, and ship faster than ever before.
The program is framework-agnostic by design. Whether you work in Python (Django), Node.js, Laravel, ASP.NET Core, Go, or Rust — the AI-native workflow you build here transfers across every stack you will ever use. By the end you will understand architecture and AI-augmented problem solving — not just syntax.
💡 Why This Program Matters
AI has fundamentally changed what a single developer can ship. Work that once required a team of five engineers over two months can now be done by one developer in two weeks — if they know how to work with AI properly. This program teaches you exactly that:
📚 Curriculum — Module Breakdown
Before writing a single line of code, you set up the full AI-augmented development environment and learn to use it fluently. This phase runs throughout the entire program — every subsequent phase uses these tools.
- Setting up Claude Code: CLI workflows, project context, memory, and slash commands
- Cursor IDE: codebase indexing, chat with your repo, inline edits, and multi-file refactoring
- GitHub Copilot: real-time completions, Copilot Chat, test generation, and PR descriptions
- AI-assisted project planning: writing architecture documents, ERDs, and API contracts with Claude
- Prompt engineering for developers: writing effective prompts for code generation, debugging, and code review
- AI code review workflow: using Claude to review pull requests, catch security issues, and enforce patterns
- Setting up a personal AI coding assistant with persistent project context
Target stacks: Python (Django), Node.js (Express), Golang, ASP.NET Core, Laravel — student selects one. Every topic is taught with Claude Code and Copilot active. You will use AI to scaffold, write, debug, and refactor — as a deliberate professional workflow, not as a shortcut.
- Defining real-world project goals and architecture with Claude — system design before code
- AI-assisted project setup: scaffolding folder structure, config files, and boilerplate via Claude Code
- Backend bootstrapping and database integration (PostgreSQL primary, MySQL/SQLite alternatives)
- ORM setup and AI-generated migrations, seeders, and query builders
- Designing and building RESTful APIs with AI-assisted route planning and controller generation
- GraphQL API layer — schema design with Claude, resolver scaffolding with Copilot
- Authentication and JWT security: implementing auth flows with AI, then auditing with Claude Code review
- Role-based access control (RBAC) — design the permission model with Claude, implement with Copilot
- Middleware, request validation, and error handling patterns
- Third-party API consumption (REST and GraphQL) — using Claude to map and integrate external APIs
- Payment gateway integration (Stripe / local gateways)
- Email services (SMTP, transactional email with Resend / Mailchimp)
- File uploads, storage abstraction, and S3-compatible APIs
- Logging, monitoring, and observability setup (Sentry, structured logging)
- Writing backend unit and integration tests — Claude-generated test suites, reviewed and refined
- Internationalisation and multi-language support
Target framework: Next.js 15 (App Router) with TypeScript — primary. Angular and Vue also supported for students on those stacks.
- AI-assisted project scaffolding: setting up Next.js / Angular / Vue with Cursor and Claude Code
- TypeScript-first development: using Claude to generate strongly-typed data models from your backend API
- Component architecture — designing a component library with Claude, building it with Copilot
- State management: Next.js server state, React Query / TanStack, Redux Toolkit, or Signals (Angular)
- API integration layer: typed API clients generated with Claude from your backend contracts
- Authentication on the frontend: session management, protected routes, token refresh logic
- Role-based UI: dynamic dashboards that render based on user permissions
- Reactive and dynamic forms — complex form logic designed with Claude, validated with Zod / Yup
- Data listing, filtering, sorting, and server-side pagination
- Data visualisation: charts and dashboards (ApexCharts, Recharts, Chart.js)
- Responsive UI with Tailwind CSS v4 — using Claude to generate and refine layouts from descriptions
- Performance optimisation: code splitting, lazy loading, image optimisation — Claude-audited
- Frontend testing: Playwright E2E tests scaffolded and reviewed with AI
- Deployment: Next.js on Vercel or integrated with backend on a single server
Production deployment — AI-generated Dockerfiles, AWS infrastructure setup, and automated CI/CD pipelines.
- Docker and Docker Compose — AI-generated Dockerfiles, reviewed and hardened with Claude
- Deploying full-stack application to AWS EC2 with a production-ready setup
- AWS services in practice: S3 (file storage), IAM (permissions), RDS (managed PostgreSQL), CloudWatch (logs)
- Reverse proxy setup with Nginx — config generated and optimised with Claude
- HTTPS with Let's Encrypt, environment variable management, and secrets handling
- CI/CD pipeline with GitHub Actions — workflow files scaffolded with Claude Code
- Monitoring, alerting, and backup strategies
This add-on moves beyond using AI as a coding assistant — you will build applications that are AI. Integrate LLMs, build RAG pipelines, and ship real AI-powered features into your existing full-stack application.
- LLM API integration: OpenAI, Anthropic (Claude), and Google Gemini APIs from your backend
- Prompt engineering for production: system prompts, few-shot examples, output formatting
- Building a RAG (Retrieval-Augmented Generation) pipeline from scratch
- Vector databases: setting up and querying pgvector (PostgreSQL) and Pinecone
- Document ingestion: chunking, embedding, and indexing PDFs, docs, and web content
- LLM agents with LangChain or LlamaIndex: tool use, memory, and multi-step reasoning
- Building real AI features: chatbot with context, document summariser, semantic search, content generator
- Streaming responses and real-time AI output in your frontend (Next.js Server-Sent Events)
- AI feature evaluation: testing and measuring LLM output quality
- Deploying AI features to production with cost and latency considerations
💻 Preferred Stacks — Student-Selected
The program is framework-agnostic — you will build your project in one of the following stacks. The AI workflow you develop applies to all of them equally. By the end you will be able to build, adapt, and migrate between stacks.
Python + Django
+ Next.js 15
Node.js + Express
+ Next.js 15
Golang
+ Next.js 15
ASP.NET Core
+ Angular or Next.js
Laravel
+ Inertia.js / Vue 3
Rust + Axum
+ Next.js 15
🛠️ AI Tools Used Throughout
Claude Code
Architecture planning, code generation, multi-file refactoring, debugging, and security review — all through natural conversation in the terminal.
Cursor IDE
AI-native editor with codebase-aware chat, inline edits, and multi-file context. The primary coding environment throughout the program.
GitHub Copilot
Real-time code completions, test generation, PR descriptions, and Copilot Chat for instant in-editor assistance.
Docker + AWS + GitHub Actions
Containerisation, cloud deployment on EC2/S3/RDS, and automated CI/CD pipelines — all configured with AI assistance throughout.
📅 Schedule & Timings
Weekday Groups
Weekend Groups
📍 Location: In-house training in Islamabad · 📱 Online option available for out-of-city participants