This practical course guides learners through building real-world Generative AI applications using LangChain, Ollama, and other local and cloud-based LLMs. Starting with the fundamentals of Generative AI, you will quickly move into hands-on tutorials that demonstrate how to run LLMs locally, build chatbots, and create database-integrated AI applications.

The course covers LangChain in depth, showing how to design AI workflows, implement Retrieval-Augmented Generation (RAG) pipelines, and integrate Q&A applications with Gemini Pro and open-source models. You’ll also explore techniques for fine-tuning models versus using RAG, understanding AI and LLM agents, and leveraging modern tools to optimize performance. Practical examples include building ChatGPT clones, RAG-based Q&A systems, and AI applications that interact with databases, giving learners a complete view of end-to-end Generative AI development.

By the end of the course, you will have the skills to develop, deploy, and optimize Generative AI solutions, understand RAG and LangChain workflows, and confidently work with both cloud and local LLMs to create scalable AI applications for research, enterprise, or personal projects.