Course Overview
This intensive 12-week program is designed for IT and non-IT professionals with zero coding knowledge who want to build production-ready GenAI applications using AI-assisted coding tools (Vibe Coding). Students will learn to leverage GitHub Copilot, Cursor AI, and ChatGPT/Claude to build, deploy, and maintain AI applications from concept to production.
What Makes This Course Unique?
- No prior coding experience needed - AI writes the code for you
- 100% practical - Build real projects every week
- Production-focused - Deploy to cloud (GCP) with CI/CD
- Weekend-friendly - Designed for working professionals
- 4 Deployable Projects - Portfolio-ready by course end
Target Audience
IT professionals wanting to transition to GenAI
Business analysts interested in AI implementation
Project managers overseeing AI projects
Entrepreneurs building AI products
Students seeking GenAI careers
Non-technical professionals wanting to code with AI
Anyone curious about AI-assisted development
Course Structure
Phase 1: Foundations (Weeks 1-4)
Learn AI-assisted coding, databases, and build first GenAI application
Phase 2: DevOps & Cloud (Weeks 5-8)
Master Docker, CI/CD, and GCP deployment
Phase 3: Advanced & Production (Weeks 9-12)
Build advanced features, optimize, and create portfolio
Detailed Weekly Curriculum
Session 1 - Development Environment Setup
Duration: 2.5 hours
- Course introduction and expectations
- What is Vibe Coding?
- Install Cursor IDE / VS Code
- Setup GitHub Copilot
- Install Python, Git, and basic tools
- First AI-assisted code - "Hello World"
Assignment: Build a simple calculator app using Copilot (Comments → Code workflow)
Session 2 - Database Setup & First Project
Duration: 2.5 hours
- Database basics explained simply
- Install PostgreSQL + pgAdmin
- Install MongoDB + Compass
- SQL basics using AI
- First database operations
Assignment: Create a "Contact Manager" CLI app with SQLite database using vibe coding
Session 3 - Understanding GenAI & APIs
Duration: 2.5 hours
- How LLMs work (simplified)
- OpenAI/Anthropic API overview
- API keys and authentication
- Making your first API call
- Prompt engineering basics
- Cost management and tokens
Assignment: Create a "Personal AI Assistant" that answers questions using OpenAI API
Session 4 - Building Your First API
Duration: 2.5 hours
- What is REST API?
- Install and setup Postman
- Flask framework introduction
- Build API using vibe coding
- Test with Postman
Assignment: Build "AI Content Generator" API with endpoints for: blog posts, social media, summaries
Session 5 - PostgreSQL Integration
Duration: 2.5 hours
- Why use databases with AI?
- SQLAlchemy ORM basics
- Vibe code database models
- CRUD operations
- Connect API to database
Assignment: Add database to your AI Content Generator - save all generated content
Session 6 - MongoDB & NoSQL
Duration: 2.5 hours
- SQL vs NoSQL - when to use what
- MongoDB basics
- PyMongo with vibe coding
- Store chat conversations
- Build chat history API
Assignment: Add MongoDB to store user preferences and conversation context
Session 7 - RAG System Basics
Duration: 2.5 hours
- What is RAG and why it matters
- Vector databases introduction
- Setup ChromaDB
- Create embeddings
- Build simple RAG system
Assignment: Create "AI Knowledge Base" that answers questions from uploaded documents
Session 8 - Complete Project Build
Duration: 2.5 hours
- Project architecture planning
- Vibe code complete application
- Testing with Postman
- Documentation using AI
- Project demo and review
PROJECT 1 SUBMISSION: Deploy locally, create README, record demo video (2 min)
Session 9 - Git Fundamentals
Duration: 2.5 hours
- Why version control matters
- Git basics - the mental model
- Setup Git and GitHub
- Basic Git commands
- Push your first project
- Branching and merging
Assignment: Push all previous projects to GitHub with proper README files
Session 10 - GitHub Actions CI/CD Intro
Duration: 2.5 hours
- What is CI/CD?
- GitHub Actions overview
- YAML basics
- Create first workflow
- Automated testing setup
Assignment: Add CI pipeline to your GenAI chat app that runs tests automatically
Session 11 - Docker Fundamentals
Duration: 2.5 hours
- Containers vs VMs explained
- Install Docker Desktop
- Docker concepts: images, containers
- Dockerfile basics
- Vibe code your first Dockerfile
- Build and run container
Assignment: Containerize your AI chat application
Session 12 - Docker Compose & Multi-Container (Optional)
Duration: 2.5 hours
- Why Docker Compose?
- Docker Compose syntax
- Multi-container applications
- Networking and volumes
- Testing complete stack
Assignment: Create Docker Compose for your complete application stack
Session 13 - GCP Account & Cloud Run
Duration: 2.5 hours
- Cloud computing basics
- GCP free tier setup
- Install gcloud CLI
- Introduction to Cloud Run
- Deploy first container
- Configure environment variables
Assignment: Deploy your AI chat app to Cloud Run
Session 14 - Cloud Databases
Duration: 2.5 hours
- Cloud SQL vs local databases
- Create Cloud SQL instance
- MongoDB Atlas setup
- Connect from Cloud Run
- Migrate data to cloud
- Connection security
Assignment: Migrate your application to use cloud databases
Session 15 - Automated Deployment
Duration: 2.5 hours
- End-to-end deployment workflow
- GitHub secrets management
- Vibe code deployment workflow
- Build and push automation
- Deploy automation
Assignment: Setup complete CI/CD: Push to GitHub → Auto deploy to GCP
Session 16 - Testing & Monitoring
Duration: 2.5 hours
- Why testing matters
- Automation testing basics
- Vibe code tests
- GCP monitoring setup
- Logs and alerts
PROJECT 2 SUBMISSION: Production-ready GenAI app on GCP with full CI/CD
Session 17 - Securing Your API
Duration: 2.5 hours
- API security fundamentals
- Authentication methods
- API key implementation
- Rate limiting
- CORS and security headers
Assignment: Add authentication and rate limiting to your production API
Session 18 - Error Handling & Resilience
Duration: 2.5 hours
- Common API errors
- Structured error responses
- Retry logic for AI APIs
- Graceful degradation
- Health checks
- Structured logging
Assignment: Add production-grade error handling to your application
Session 19 - Streaming & Function Calling
Duration: 2.5 hours
- Why streaming matters
- Server-Sent Events (SSE)
- Implement streaming
- Function calling introduction
- Build AI agent with tools
Assignment: Add streaming responses and 3 custom tools to your AI app
Session 20 - Advanced RAG Techniques
Duration: 2.5 hours
- RAG limitations and solutions
- Chunking strategies
- Hybrid search
- Re-ranking and filtering
- Citation and sources
Assignment: Upgrade your RAG system with advanced features
Session 21 - Project Planning & Architecture
Duration: 2.5 hours
- Project selection and scope
- Architecture design with AI
- Database schema design
- API endpoint planning
- Timeline and milestones
Choose ONE Project:
- AI Document Intelligence System - Upload docs, ask questions, get insights
- AI Customer Support Agent - Email integration, ticket management, auto-responses
- AI Content Platform - Generate blogs, social posts, SEO content
- AI Learning Assistant - Personalized learning paths, quiz generation
Session 22 - Start Building
Duration: 2.5 hours
- Project setup and structure
- Vibe code core features
- Progress review
- Q&A and troubleshooting
Assignment: Complete 60% of core features by next week
Session 23 - Complete & Deploy Project
Duration: 2.5 hours
- Complete remaining features
- Frontend integration (if applicable)
- Testing thoroughly
- Deploy to GCP with CI/CD
Assignment: Final testing and documentation
Session 24 - Demo & Course Wrap-up
Duration: 2.5 hours
- Create portfolio website
- Student project presentations
- Technical blog writing
- Career guidance and next steps
- Course feedback and certification
PROJECT 3 (CAPSTONE) SUBMISSION: Complete application with deployment, documentation, demo video, and technical blog post