Developing Custom LLM Applications with RAG and Agents

Modern AI is about more than just chatting; it is about building systems that understand your specific data and perform complex tasks. This course provides a clear path for beginners to transition from using AI to building with it. You will learn how to augment language models with external knowledge and create autonomous agents that solve problems. By reading through structured lessons and practicing with code snippets, you will gain the skills to develop intelligent applications from the ground up. * Understand the fundamental architecture and terminology of Large Language Models. * Implement Retrieval-Augmented Generation (RAG) to ground AI in specific datasets. * Configure and manage vector databases for high-performance information retrieval. * Master prompt engineering patterns to guide model behavior effectively. * Design AI agents capable of planning and executing multi-step workflows. * Apply multimodal concepts to handle diverse data formats beyond simple text. The curriculum begins with essential definitions and core AI principles before moving into the practical mechanics of RAG and agentic design. This course is designed for beginners with a basic understanding of Python who want to enter the field of AI development. No prior experience with machine learning is required. Start your journey into the world of custom AI development today.