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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 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!
Duration
4 Months
Institution
IBM
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into IBM .
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$238
Total Est. Investment
$238
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Fundamentals of AI Agents Using RAG and LangChain program at IBM are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.