Fundamentals of AI Agents Using RAG and LangChain
$49
ENROLL NOWCourse Overview
What You'll Learn
- 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.
- You’ll learn about the RAG process, its applications, encoders and tokenizers, and the FAISS library for high-dimensional vector search.
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!
Course FAQs
Is this an accredited online course?
Accreditation for 'Fundamentals of AI Agents Using RAG and LangChain' is determined by the provider, IBM. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
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How do I enroll in this online school program?
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