Basic to Advanced: Retreival-Augmented Generation (RAG)
Multi-modal RAG Stack: A Hands-on Journey Through Vector Stores, LLM Integration, and Advanced Retrieval Methods
4.52 (850 reviews)
4 754
students
2.5 hours
content
Feb 2025
last update
$79.99
regular price
What you will learn
Build three professional-grade chatbots: Website, SQL, and Multimedia PDF
Master RAG architecture and implementation from fundamentals to advanced techniques
Run and optimize both open-source and commercial LLMs
Implement vector databases and embeddings for efficient information retrieval
Create sophisticated AI applications using LangChain framework
Deploy advanced techniques like prompt caching and query expansion
Understand how to deploy on AWS EC2 (Basic Guide)
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Our Verdict
This multi-modal RAG Stack course offers an engaging, hands-on journey through vector stores, LLM integration, and advanced retrieval techniques. While the fast pace and video presence may pose minor challenges for some learners, mastering RAG fundamentals and gaining practical experience with real-world examples largely outweigh these concerns. Recommended for developers seeking a comprehensive understanding of production-ready AI applications.
What We Liked
- In-depth exploration of Retrieval-Augmented Generation (RAG) and LangChain
- Hands-on practice with three professional-grade chatbot builds
- Mastery of RAG architecture, implementation, and optimization
- Comprehensive coverage of vector databases, embeddings, and managed database integration
Potential Drawbacks
- Accelerated pace may challenge some learners; prior Python knowledge beneficial
- Instructor's video presence can be distracting; text-based resources preferred by some
- Limited focus on specific use cases and application industries
- Sporadic repetition in course content—minor improvements possible
6181385
udemy ID
13/09/2024
course created date
06/11/2024
course indexed date
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