Unlock the Power of Retrieval Augmented Generation (RAG) β New Course Available! π
Discover the latest techniques in RAG with expert AI engineer Zain H. Enroll now to enhance your AI skills and stay ahead in the field. Learn more: https://bit.ly/3GKWqrY

DeepLearningAI
5.9K views β’ Jul 16, 2025

About this video
Learn more: https://bit.ly/3GKWqrY
Weβre thrilled to announce the launch of a new course: Retrieval Augmented Generation (RAG), taught by AI engineer Zain Hasan, and available on Coursera.
This hands-on course shows you how to build production-ready RAG systems, connecting language models to external data sources to improve accuracy, reduce hallucinations, and support real-world use cases.
You'll move beyond prototype-level LLM apps to build full RAG pipelines that are scalable, adaptable, and grounded in real context. In detail, youβll:
- Combine retrievers and LLMs using tools like Weaviate, Together.AI, and Phoenix
- Apply effective retrieval such as keyword search, semantic search, and metadata filtering, and know when to use each
- Evaluate system performance, balance cost-speed-quality tradeoffs, and prep your pipeline for deployment
Youβll work with real-world datasets from domains like healthcare, media, and e-commerce, gaining a practical foundation and engineering judgment you can apply in production settings.
This course is designed for software engineers, ML practitioners, and technical professionals building with LLMs. If your applications require accuracy, traceability, and relevance, this course will show you how to get there with RAG.
Enroll now: https://bit.ly/3GKWqrY
Weβre thrilled to announce the launch of a new course: Retrieval Augmented Generation (RAG), taught by AI engineer Zain Hasan, and available on Coursera.
This hands-on course shows you how to build production-ready RAG systems, connecting language models to external data sources to improve accuracy, reduce hallucinations, and support real-world use cases.
You'll move beyond prototype-level LLM apps to build full RAG pipelines that are scalable, adaptable, and grounded in real context. In detail, youβll:
- Combine retrievers and LLMs using tools like Weaviate, Together.AI, and Phoenix
- Apply effective retrieval such as keyword search, semantic search, and metadata filtering, and know when to use each
- Evaluate system performance, balance cost-speed-quality tradeoffs, and prep your pipeline for deployment
Youβll work with real-world datasets from domains like healthcare, media, and e-commerce, gaining a practical foundation and engineering judgment you can apply in production settings.
This course is designed for software engineers, ML practitioners, and technical professionals building with LLMs. If your applications require accuracy, traceability, and relevance, this course will show you how to get there with RAG.
Enroll now: https://bit.ly/3GKWqrY
Video Information
Views
5.9K
Likes
118
Duration
1:40
Published
Jul 16, 2025
User Reviews
4.6
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