Udemy - Generative AI with AI Agents & MCP for Developers

Master Generative AI, Model Context Protocol (MCP), and build cutting-edge AI Agent Systems with Python & LLMs
What you'll learn
Understand the fundamentals of Generative AI and Large Language Models (LLMs)
Design and build scalable Generative AI applications using Advanced Gen AI Application Architecture
Master Retrieval-Augmented Generation (RAG) techniques for smarter applications
Explore and leverage orchestration frameworks like LangChain and LlamaIndex
Gain hands-on experience with LangChain Expression Language (LCEL) and its Ecosystem
Develop strong Prompt Engineering skills to optimize LLM outputs
Build end-to-end Gen AI applications across multiple complexity levels (Beginner to Professional)
Implement AI Agent and Multi-Agent systems for advanced automation
Integrate Multimodal data (text, image, etc.) into Generative AI applications
Learn LLMOps (Large Language Model Operations) for efficient deployment and management
Deploy Generative AI applications to production using CI/CD pipelines
Understand and implement Model Context Protocol (MCP) for context-aware applications
Fine-tune Large Language Models (LLMs) to fit custom project needs
Work on real-world Generative AI projects to solidify practical knowledge
Requirements
Basic understanding of Python programming
Familiarity with fundamental concepts of machine learning (helpful but not mandatory)
No prior experience with Generative AI or LLMs required
Curiosity and willingness to learn cutting-edge AI technologies
Description
This hands-on course teaches you how to build professional level Generative AI Application, intelligent, autonomous AI Agents using MCP (Model Context Protocol) and modern LLM frameworks.Whether you're an AI beginner or an experienced developer, this course will take you step-by-step through the tools, strategies, and architectures that power modern GenAI applications.What You'll Learn:- Introduction to Generative AI and its role in modern development- Introduction to Large Language Models (LLMs) and how they power intelligent applications- Generative AI Architecture Basics - understand the core components of a Gen AI application- Advanced Gen AI Application Architecture for scalable and modular systems- How to apply the Retrieval-Augmented Generation (RAG) technique for enhanced responses- Choosing the Right Orchestration Framework for building LLM-powered apps- LangChain - A modern framework for LLM orchestration- LangChain Expression Language (LCEL) - Build AI flows with clean, declarative syntax- Deep dive into the LangChain Ecosystem for agents, tools, memory, and chains- Mastering Prompt Engineering - Learn to craft optimal prompts for LLMs- Level 1 Gen AI Applications - Basic AI-powered tools and assistants- LlamaIndex - An alternative to LangChain for RAG and LLM app orchestration- LLMOps (Large Language Model Operations) - Manage and monitor LLM Apps- Level 2 Gen AI Applications - Build intermediate systems with memory, tools, and retrieval- Develop Multimodal Gen AI Applications (text, image, audio integration)- Build and deploy AI Agents & Multi-Agent Systems using orchestration frameworks- Level 3 (Professional) Gen AI Applications - Real-time, scalable, production-ready systems- CI/CD for Gen AI - Deploy your Gen AI apps with automated pipelines- Understand and implement MCP (Model Context Protocol) - Hands-on Projects - From AI assistants to autonomous agents and RAG-powered apps- Fine-tuning LLMs for domain-specific use cases and better performance
Who this course is for
Developers and software engineers interested in building Generative AI applications
Data scientists and machine learning engineers looking to integrate LLMs into real-world projects
AI enthusiasts eager to explore cutting-edge concepts like AI Agents, MCP, RAG, and LLMOps
Students and researchers who want practical experience in developing AI-powered applications
nyone curious about building end-to-end, production-ready Generative AI systems, from beginner to advanced levels
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