A 12-week intensive self-study program to master modern Python development, cloud infrastructure, and AI applications.

Duration: 12 weeks (July 10 - October 2, 2025) Time Commitment: Full-time (9 AM - 5 PM, Monday-Friday) Background: 20 years of Python experience, expanding into modern web development and AI

• Web Development: FastAPI, SQLAlchemy, Pydantic
• Data Engineering: Pandas, data pipelines
• Cloud Infrastructure: AWS (S3, Lambda, EKS)
• DevOps: Docker, GitHub Actions, CI/CD
• AI/ML: LangChain, OpenAI API, FAISS vector stores

• Building production-ready REST APIs
• Database integration and migrations
• Authentication and middleware

• Advanced data manipulation
• Performance optimization
• ETL pipeline development

• S3 for object storage
• Lambda for serverless computing
• EKS for container orchestration

• Automated testing and deployment
• Multi-environment pipelines
• Infrastructure as Code

• LLM integration patterns
• RAG implementation
• Vector databases with FAISS

• Full-stack AI-powered analytics platform
• Integration of all learned technologies

├── week01-02-fastapi/
│   ├── tutorials/
│   ├── projects/
│   └── notes.md
├── week03-04-pandas/
├── week05-07-aws/
├── week08-github-actions/
├── week09-11-ai-agents/
├── week12-portfolio-project/
└── resources/
    └── useful-links.md

• Book Inventory API (FastAPI)
• Data Pipeline Service (Pandas + FastAPI)
• Serverless Image Processor (S3 + Lambda)
• Kubernetes Deployment (EKS)
• AI-Powered Analytics Platform

• 🔄 FastAPI fundamentals

• Environment setup
• FastAPI basics
• Path parameters and routing
• Request/Response models
• Dependency injection

• FastAPI Official Documentation
• SQLAlchemy 2.0 Documentation
• AWS Python SDK (Boto3)
• LangChain Documentation

• TestDriven.io FastAPI Course
• AWS EKS Workshop
• Building LLM Applications

By the end of this program, I will be able to:

1. Design and build scalable REST APIs with FastAPI
2. Implement complex data processing pipelines
3. Deploy applications to AWS using modern DevOps practices
4. Build AI-powered applications with LLMs
5. Create full-stack applications from conception to production

• LinkedIn: [Your LinkedIn]
• Email: [Your Email]
• Portfolio: [Coming Soon]

• Set up development environment
• Started FastAPI tutorial
• Created first API endpoints

This repository documents my journey from experienced Python developer to full-stack cloud and AI engineer. Feel free to explore the code and reach out if you have questions or opportunities!