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Learner Reviews & Feedback for Retrieval Augmented Generation (RAG) by DeepLearning.AI

4.8
stars
56 ratings

About the Course

Retrieval Augmented Generation (RAG) improves large language model (LLM) responses by retrieving relevant data from knowledge bases—often private, recent, or domain-specific—and using it to generate more accurate, grounded answers. In this course, you’ll learn how to build RAG systems that connect LLMs to external data sources. You’ll explore core components like retrievers, vector databases, and language models, and apply key techniques at both the component and system level. Through hands-on work with real production tools, you’ll gain the skills to design, refine, and evaluate reliable RAG pipelines—and adapt to new methods as the field advances. Across five modules, you'll complete hands-on programming assignments that guide you through building each core part of a RAG system, from simple prototypes to production-ready components. Through hands-on labs, you’ll: - Build your first RAG system by writing retrieval and prompt augmentation functions and passing structured input into an LLM. - Implement and compare retrieval methods like semantic search, BM25, and Reciprocal Rank Fusion to see how each impacts LLM responses. - Scale your RAG system using Weaviate and a real news dataset—chunking, indexing, and retrieving documents with a vector database. - Develop a domain-specific chatbot for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset. - Improve chatbot reliability by handling real-world challenges like dynamic pricing and logging user interactions for monitoring and debugging. - Develop a domain-specific chatbot using open-source LLMs hosted by Together AI for a fictional clothing store that answers FAQs and provides product suggestions based on a custom dataset. You’ll apply your skills using real-world data from domains like media, healthcare, and e-commerce. By the end of the course, you’ll combine everything you’ve learned to implement a fully functional, more advanced RAG system tailored to your project’s needs....

Top reviews

RS

Aug 14, 2025

I learnt quite a bit about LLMs, vector databases, RAG and various terms associated with this space. I came out better informed and hopefully learn more and implement these things in my projects

AD

Aug 13, 2025

Fabulous explanation of basic to advanced RAG concept. A mandatory course for all the AI geeks out there.

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1 - 13 of 13 Reviews for Retrieval Augmented Generation (RAG)

By Seelam S R

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Jul 29, 2025

This course gave me a solid understanding of Retrieval Augmented Generation, combining theory with hands-on projects using real-world tools like Weaviate and Phoenix. I now feel confident building scalable RAG systems and optimizing them for accuracy, latency, and cost."

By Max G

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Jul 22, 2025

This course has been great to refresh my knowledge and deepen it. The course really helped to focus on the crucial building blocks for RAG systems and made it as easy as possible to follow along and learn.

By Ravi S

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Aug 14, 2025

I learnt quite a bit about LLMs, vector databases, RAG and various terms associated with this space. I came out better informed and hopefully learn more and implement these things in my projects

By Raúl A

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Aug 12, 2025

Excelente curso! El material abarca más de lo fundamental del tema y te va guiando por los conceptos de una manera fluida.

By Aritra D

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Aug 13, 2025

Fabulous explanation of basic to advanced RAG concept. A mandatory course for all the AI geeks out there.

By Prakash j

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Aug 15, 2025

The content is excellent, and Zain explains everything with calm clarity and a well-structured approach.

By Juan J E G

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Jul 27, 2025

Very good and enjoyed the material. The instructor really understands the field and explains very well.

By Ben D C

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Aug 2, 2025

Great step-by-step introduction on RAG systems and get deeper understanding of its components.

By Michael F

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Jul 28, 2025

Excellent course! Great detail and very well explained.

By 许乐龙

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Aug 18, 2025

Great course! Not just RAG, but proper dose of supportive topics about search, LLM, etc. Every word carries valuable information. Thanks!

By Sebastian R

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Aug 5, 2025

Amazing course on RAG systems at production scale.

By Robin F

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Aug 21, 2025

The concepts presented in this course were insightful and valuable, and I also appreciated the way the modules were structured. However, the overall teaching approach felt somewhat limited — it mainly involved clicking through steps and filling in pre-prepared code snippets. There were few opportunities for open-ended problem-solving or creating original code solutions. In many cases, simply copy-pasting from earlier cells or making minor edits to previous prompts was sufficient, which reduced the challenge and depth of the exercises.

By Alon T

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Aug 10, 2025

Overly technical, lacks conceptual grounding in generative models.