Generative AI Engineering: LLMs, RAG, and Agentic Systems

Learn to design and implement GenAI workflows, multi-agent systems, LangChain, LangGraph, MCP, and model fine-tuning What you'll learn: Master Generative AI foundations, how LLMs work, and how modern AI systems are designed and applied in real-world products.Design and build end-to-end Generative AI systems using LLMs, retrieval pipelines, tools, and agentic workflows.Implement Retrieval-Augmented Generation (RAG), embeddings, vector search, reranking, and advanced retrieval patterns.Build AI agents, multi-step reasoning systems, and multi-agent workflows using LangChain and LangGraph.Develop production-style applications with structured outputs, validation, memory, and human-in-the-loop workflows.Create MCP servers and clients to connect LLMs to real tools, services, and enterprise systems.Fine-tune and optimize models using Hugging Face workflows, dataset preparation, and quantization techniques.Apply system-level best practices for cost, reliability, scalability, and responsible deployment of GenAI applications. 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 LearnUnderstand Generative AI foundations and