Ready to build modern AI-powered applications instead of just making simple API calls ?

Welcome to The Complete FastAPI Generative AI Bootcamp, where you'll learn how to build production-ready AI applications using FastAPI, Large Language Models (LLMs), and modern AI engineering techniques.

This course goes far beyond basic ChatGPT integrations. You'll learn how real-world AI applications are built from simple AI assistants to intelligent AI Agents with long-term memory, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), guardrails, and scalable multi-provider AI architectures.

Every concept is taught through practical coding sessions and real-world projects, giving you the skills needed to build AI products for clients, startups, or your own SaaS business.

Whether you're a Python developer, FastAPI developer, backend engineer, or someone looking to transition into AI Engineering, this course will provide the practical experience needed to build production-ready AI applications.

Note:- This course is currently On Air which means I will keep updating the course till last August. Its just like Web Series every other day you will get new episode.

What You'll Learn

• Build AI Applications with FastAPI - Learn how to integrate modern LLMs into FastAPI applications using the latest OpenAI SDK and production-ready architecture.
• Master Prompt Engineering - Write effective prompts, system prompts, few-shot prompts, and structured prompts to produce reliable AI responses.
• Streaming & Structured Outputs -Build AI applications with streaming responses, structured outputs, JSON schemas, and type-safe responses.
• Function Calling & AI Tools - Allow AI models to interact with external APIs, databases, and business logic using function calling and tools.
• Build AI Agents - Develop autonomous AI Agents capable of reasoning, planning, tool usage, and solving complex tasks.
• Agentic AI Workflows - Create multi-step AI workflows where multiple agents collaborate to complete real-world business processes.
• Retrieval-Augmented Generation (RAG) - Implement embeddings, vector databases, semantic search, document indexing, and conversational RAG systems.
• Long-Term Memory Systems - Build AI applications with short-term memory, episodic memory, semantic memory, procedural memory, and intelligent memory retrieval.
• Model Context Protocol (MCP) - Create MCP servers, MCP tools, resources, prompts, and connect AI agents using the latest Model Context Protocol.
• AI Evaluation & Guardrails - Improve AI reliability by implementing evaluation pipelines, validation, safety checks, and guardrails.
• Multi-Provider AI Architecture - Design scalable AI applications supporting OpenAI, Anthropic, Gemini, Groq, Ollama, and other LLM providers through a clean architecture.
• Build Production-Ready Projects - Develop complete AI applications using modern software architecture, FastAPI best practices, and reusable code that can be deployed in real-world environments.

Why Learn GEN AI Engineering?

Artificial Intelligence is transforming every software industry.

Companies are no longer looking for developers who can simply call an AI API they need engineers who can build complete AI systems.

In this course, you'll learn the technologies powering modern AI products, including:

• AI Engineering
• Large Language Models (LLMs)
• AI Agents
• Agentic AI
• Retrieval-Augmented Generation (RAG)
• Model Context Protocol (MCP)
• Long-Term Memory
• Function Calling
• Structured Outputs
• Streaming
• Guardrails
• Multi-Provider AI Architecture
• Production FastAPI Development

Why Take This Course?

✅ Hands-on coding with real-world projects

✅ Production-ready architecture and best practices

✅ Learn the latest OpenAI SDK and modern AI workflows

✅ Build reusable AI backend systems with FastAPI

✅ No unnecessary theory focus on practical implementation

✅ Create portfolio-ready AI applications

✅ Perfect for developers, freelancers, and SaaS founders

Who This Course Is For

• Python developers who want to build AI-powered applications.
• Beginner FastAPI developers who want to build AI applications.
• Backend developers interested in AI Engineering.
• Software engineers looking to integrate LLMs into production systems.
• Freelancers building AI solutions for clients.
• Entrepreneurs and SaaS founders creating AI products.
• Anyone who wants to move beyond basic ChatGPT API tutorials and build production-ready AI systems.

Prerequisites

• Basic Python programming knowledge
• Basic understanding of FastAPI is recommended
• No prior AI or Machine Learning experience is required