Understanding how to enhance the capabilities of AI and machine learning systems is a valuable skill. One method is Retrieval-Augmented Generation (RAG), a powerful technique that combines retrieval-based methods with generative models to create more accurate and contextually relevant responses.
We just published a course on the freeCodeCamp.org YouTube channel that will teach you all about Retrieval-Augmented Generation (RAG). Created by Paulo Dichone, this course starts with the basics and progressively covers more advanced aspects, ensuring a comprehensive understanding of RAG and its practical applications. You'll learn the fundamental concepts and components of RAG, build a system for chatting with documents, explore advanced techniques, and understand the drawbacks of naive RAG approaches.
The course begins with an introduction, outlining the course content and objectives, setting the stage for your journey into RAG. You’ll learn the essential principles of Retrieval-Augmented Generation, including how it integrates retrieval mechanisms with generative models. This foundation will help you grasp the various components that make up a RAG system and understand their roles and interactions.
As the course progresses, you'll dive deeper into RAG, examining its inner workings and intricacies. This deep dive will prepare you for a hands-on project where you'll build a RAG system designed to interact with documents, enhancing your practical skills. This practical application is crucial for solidifying your understanding and ability to implement RAG in real-world scenarios.
Following this, the course introduces more sophisticated RAG techniques that can improve system performance and accuracy. You’ll gain insights into the limitations and common issues associated with simple, naive RAG implementations. This understanding is critical, as it highlights the importance of advanced techniques in overcoming these challenges.
One of the advanced techniques you'll learn about is query expansion, which involves generating more relevant answers through expanded queries. This section includes both theoretical explanations and hands-on projects, allowing you to apply query expansion techniques practically. The course also explores using multiple queries to further enhance the effectiveness of a RAG system, providing another hands-on project to deepen your understanding.
To test your skills and knowledge, the course presents a challenge that lets you implement what you've learned. Finally, the course concludes with a look at potential next steps and further learning opportunities in the field of RAG.
By the end of this course, you'll have a solid understanding of Retrieval-Augmented Generation, equipped with the knowledge and skills to build and enhance your own RAG systems. Watch the full course on the freeCodeCamp.org YouTube channel (2-hour watch).