Agentic AI Projects: FastAPI, MCP, AWS Deploy & Gemini 3 (Udemy.com)

Welcome to the most comprehensive Agentic AI projects course on Udemy for 2026 — focused on building, deploying, and scaling real-world AI agents in production.

Learn to architect and ship 10 production-grade AI Agent projects using LangChain v1, LangGraph, Google Gemini 3, MCP (Model Context Protocol), FastAPI, Streamlit, and AWS EC2 — the exact stack powering the next generation of autonomous AI systems.

This course is not another "build a chatbot" tutorial. It is the production deployment companion you need after learning LangChain fundamentals. Every module ends with working, deployable code you can adapt for your own product, client, or portfolio.

Who is teaching this course

I'm Laxmi Kant Tiwari, founder of KGP Talkie, with over a decade of AI and Machine Learning industry experience including senior AI engineering at Linedata. I've taught 160,000+ students across YouTube and Udemy, and I build and deploy the exact systems I teach. No fluff, no filler, no recycled Medium articles — just production-grade code and architecture you can ship.

The 10 Production AI Agent Projects You Will Build

1. Live Hotel Search Agent — Airbnb MCP server integration with real-time search

2. Travel Planner Agent — Google Calendar MCP with memory and multi-tool orchestration

3. Code Execution Agent — Secure E2B sandbox for data analysis (Apple, Google, IMDB, Titanic datasets)

4. Google Sheets + Finance Analyzer Agent — Yahoo Finance MCP with Sheets read and write

5. Gmail Daily Briefing Agent — Automated email summarization and action extraction

6. Personal AI Assistant on AWS EC2 — LangChain Agent Chat UI deployed to production

7. AI Agent REST API Gateway — FastAPI with Pydantic, CORS, and Swagger UI

8. Full-Stack AI Assistant — Streamlit + FastAPI with real-time response streaming

9. Cloud-Deployed Full-Stack Agent — End-to-end AWS EC2 deployment with security hardening

10. MySQL E-commerce Analyst Agent — TiDB + MCP + FastAPI streaming server

What Makes This Course Different

• LangChain v1 and Gemini 3 — the freshest possible stack; most courses still teach deprecated v0.x APIs

• Real MCP server integrations — not toy examples. Airbnb, Gmail, Google Calendar, Google Sheets, Yahoo Finance, MySQL

• Actual AWS EC2 deployment walkthroughs — from instance launch to production security configuration

• Production patterns — model fallback, error handling, guardrails, HITL, streaming, context offloading

• 26+ hours of hands-on video — every line of code explained, every architecture decision justified