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LLM Engineering with RAG: Optimizing AI Solutions
Coursera Instructor Network

LLM Engineering with RAG: Optimizing AI Solutions

 Ashraf S. A. AlMadhoun
Starweaver Instructor Team

Instructors: Ashraf S. A. AlMadhoun

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Integrate LLMs with enterprise data Applications.

  • Evaluate RAG techniques to improve the accuracy and efficiency of AI retrieval and generation processes.

  • Refine prompts to optimize the quality and relevance of AI-generated responses.

  • Deploy scalable LLM-powered solutions to address complex real-world enterprise challenges.

Details to know

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Recently updated!

May 2025

Assessments

1 assignment

Taught in English

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There is 1 module in this course

In this course, you’ll learn how to integrate enterprise data with advanced large language models (LLMs) using Retrieval-Augmented Generation (RAG) techniques. Through hands-on practice, you’ll build AI-powered applications with tools like LangChain, FAISS, and OpenAI APIs. You’ll explore LLM fundamentals, RAG architecture, vector search optimization, prompt engineering, and scalable AI deployment to unlock actionable insights and drive intelligent solutions.

What's included

14 videos7 readings1 assignment1 peer review2 plugins

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Instructors

 Ashraf S. A. AlMadhoun
Coursera Instructor Network
2 Courses568 learners

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