This course provided a clear and structured introduction to Retrieval-Augmented Generation and its practical applications. I appreciated the balance between theory and hands-on projects, especially the use of LangChain and FAISS for building real-world solutions like document summarization and chatbots. The step-by-step explanations helped me understand how to integrate vector databases, prompt templates, and LLMs into functional systems. I now feel confident to start developing my own RAG-based applications and explore more advanced use cases. A great starting point for anyone interested in applied AI and automation.

The Coure content gives a Comprahensive understandung of RAG

Excellent. Well done. Short and Sweet -- and practical.

interesting

excelente!

The course provides a clear and accessible introduction to RAG, explaining how retrieval systems and large language models (LLMs) work together to generate more accurate and contextually relevant outputs. What I loved most was the balance of theory and hands-on practice. The two real-world applications projects such as Invoice Parsing and The HR Policy ChatBot, were very engaging and helped contextualize the theoretical concepts. The instructor’s clear explanations and beginner-friendly approach made it easy to follow along, even with more complex topics. This course is a great starting point for anyone looking to understand and work with Retrieval-Augmented Generation systems. It’s informative, practical, and offers a strong foundation for further exploration in the field.

I cannot find any code snippets.