Generative AI Engineering: LLMs, RAG, and Agentic Systems

About this course

Build Real-World Generative AI Systems with LLMs, RAG, and AI AgentsGo beyond prompts and chatbots. This course takes you on a complete, progressive journey from Generative AI fundamentals to advanced system-level techniques.

You’ll start by mastering the core concepts of LLMs, NLP, and AI model behavior, then move into applying RAG pipelines, vector search, and prompting patterns. Finally, you’ll tackle advanced topics such as agentic systems, multi-agent orchestration, LangGraph workflows, MCP, and model fine-tuning.

Learn to design and implement intelligent AI workflows and system components using multiple LLMs, LangChain, LangGraph, embeddings, and agentic reasoning—without the pressure of building full production applications.

Skip the beginner fluff—this is for engineers, architects, and technical founders who want to understand how modern GenAI systems are actually structured and engineered.

What You Will Learn

Understand Generative AI foundations and how LLMs work, including OpenAI, Claude, Gemini, and Hugging Face models.

Apply RAG pipelines, vector search, embeddings, and structured outputs to create robust AI workflows.

Learn prompting techniques, in-context learning, and fine-tuning strategies for advanced LLM behavior.

Build and test agentic and multi-agent systems using LangChain and LangGraph.

Explore MCP servers and clients to integrate LLM reasoning with external tools and services.

Understand system-level best practices for efficiency, scalability, cost, and responsible AI deployment.

Hands-On Learning

This is a learning-by-doing course

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.