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HomeCoursesAdvanced RAG Techniques: Choosing the Right Approach

Intermediate

4h

Advanced RAG Techniques: Choosing the Right Approach
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Learn advanced RAG techniques in this advanced RAG course. Explore pre- and post-retrieval optimization with LangChain, and build intelligent, scalable applications with hands-on projects.
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28 Lessons
4 Quizzes
1 Project
Certificate of Completion
Overview
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Overview

Master advanced retrieval-augmented Generation (RAG) techniques in this comprehensive course for experienced learners. You’ll gain hands-on experience implementing advanced RAG systems with LangChain, equipping you to create intelligent, efficient AI applications. The course begins by revisiting the core principles of RAG and then dives into pre-retrieval optimization techniques, focusing on strategies like indexing and query formulation. Next, you’ll explore post-retrieval optimization methods, such as RA...Show More
Master advanced retrieval-augmented Generation (RAG) techniques in this comprehensive course for experienced learners. You’ll ga...Show More

WHAT YOU'LL LEARN

A deep understanding of retrieval-augmented generation (RAG) and its ability to enhance the accuracy of large language models
Mastery of advanced RAG implementation approaches and the ability to choose the right method for specific applications
Hands-on experience building RAG systems using LangChain
Proficiency in pre-retrieval optimization techniques, such as indexing and query formulation
An understanding of post-retrieval optimization methods, including RAG-Fusion and Cross Encoder reranking
The ability to design and implement RAG-based chatbots and other intelligent systems
A deep understanding of retrieval-augmented generation (RAG) and its ability to enhance the accuracy of large language models

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TAKEAWAY SKILLS

Generative AI

Natural Language Processing

Content

1.

Getting Started

2 Lessons

Get familiar with RAG to enhance factual accuracy and build robust NLP applications.

5.

Advanced RAG: Post-Retrieval Process

4 Lessons

Enhance RAG response quality with post-retrieval optimization, RAG-fusion, and Cross Encoder reranking.

6.

Conclusion

1 Lessons

See how it works integrating RAG techniques for enhanced NLP applications and community engagement.
Certificate of Completion
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