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Overview
The course “RAG and Fine-Tuning Explained” provides a clear and practical introduction to two powerful techniques in natural language processing (NLP): Retrieval-Augmented Generation (RAG) and fine-tuning. Designed for data scientists, AI practitioners, and developers, this course demystifies how these methods enhance the performance and customization of language models. Participants will learn about RAG, a hybrid approach that combines retrieval-based information access with generative models to produce more accurate and context-aware responses. The course explains how RAG retrieves relevant documents or...
Syllabus
Introduction
- RAG, fine-tuning, and the enterprise
1. RAG and Fine-Tuning
- How LLMs work
- Context makes all the difference
- RAG: Retrieval Augmented Generation
- The RAG flow
- Embeddings:ing AI understand data
- Knowledge graphs
- Fine-tuning
- RAFT: RAG with fine-tuning
2. Conclusion
- Tying it all together
Instructor
Morten Rand-Hendriksen
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