Fundamentals of AI Agents Using RAG and LangChain
Business demand for technical gen AI skills is exploding, and AI engineers who can work with large language models (LLMs) are in high demand. This Fundamentals...
By Abdul Fatir on Coursera
About This Course
Business demand for technical gen AI skills is exploding, and AI engineers who can work with large language models (LLMs) are in high demand. This Fundamentals of Building AI Agents using RAG and LangChain course builds job-ready skills that will fuel your AI career. In this course, you’ll explore retrieval-augmented generation (RAG), prompt engineering, and LangChain concepts. You’ll learn about the RAG process, its applications, encoders and tokenizers, and the FAISS library for high-dimensional vector search. Then, you’ll apply in-context learning and advanced prompt engineering techniques, including prompt templates and example selectors, to generate accurate responses. You’ll also work with LangChain’s tools, components, document loaders, retrievers, chains, and agents to simplify LLM-based application development. Through hands-on labs, you’ll develop AI agents that integrate LLMs, LangChain, and RAG technologies. You will also complete a real-world project you can showcase in interviews. A comprehensive cheat sheet and glossary are included to reinforce your learning. Enroll today and build in-demand generative AI skills in just 8 hours!
Topics Covered
Frequently Asked Questions
How much does Fundamentals of AI Agents Using RAG and LangChain cost?
Visit the Fundamentals of AI Agents Using RAG and LangChain course page for current pricing and available discounts.
Who teaches Fundamentals of AI Agents Using RAG and LangChain?
Fundamentals of AI Agents Using RAG and LangChain is taught by Abdul Fatir, IBM.
What skill level is Fundamentals of AI Agents Using RAG and LangChain for?
This course is designed for beginner learners.
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