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Building AI Agents with RAG and LangChain

Premium
IntermediateCourse

Gain job-ready skills in building AI agents in just 2 weeks. Plus, valuable practical experience and a credential. Build familiarity with RAG and LangChain.

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

  • Retrieval Augmented Generation (RAG), In-context Learning And Prompt Engineering, LangChain, Vector Databases, Chatbots

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 6 hours

Platform

  • SkillsNetwork

Last Update

  • April 22, 2025
About this Course
This Building AI Agents with RAG and LangChain course teaches you the skills you need for your AI career.  
 
You will learn: 
 
  • Job-ready skills in 2 weeks, plus you’ll get practical experience employers look for on a resume and an industry-recognized credential 
  • Apply the fundamentals of in-context learning and advanced methods of prompt engineering to enhance prompt design 
  • Explore key concepts of LangChain, LangChain tools, components, chat models, chains, and agents 
  • Apply RAG, PyTorch, Hugging Face, LLMs, and LangChain technologies for different applications 
 
 
 
Course Overview 
 
Business demand for technical Generative AI skills is exploding and Generative AI engineers who can work with large language models (LLMs) are in high demand. This Building AI Agents with RAG and LangChain intermediate-level course builds job-ready skills that will fuel your AI career in just 2 weeks.   
 
In this course, you’ll explore retrieval-augmented generation (RAG), prompt engineering, and LangChain concepts. You’ll look at RAG, its applications, processes, encoders, tokenizers, and the Facebook AI Similarity Search (Faiss) library. Then, you’ll apply in-context learning and prompt engineering to design and refine prompts for accurate responses. Plus, you’ll explore LangChain tools, components, and chat models, and work with LangChain to simplify the application development process using LLMs.  
 
Additionally, you’ll get valuable hands-on practice in online labs developing applications using integrated LLM, LangChain, and RAG technologies. Plus, you’ll complete a real-world project you can discuss in interviews. 
 
If you’re keen to boost your resume and extend your generative AI skills for applying transformer-based LLMs, ENROLL today and build job-ready skills in 8 hours.


Course Syllabus

Module 0: Welcome

·         Video:  Course Introduction
·         Reading:General Information
·         Reading:Learning Objectives and Syllabus
·         Reading:Grading Scheme
·         Reading: Specialization Overview
·         Reading: Helpful Tips for Course Completion

Module 1: RAG Framework

·         Reading: Module 1 Introduction and Learning Objectives
·         Video: RAG
·         Video: RAG, Encoders, and FAISS
·         Lab: RAG with Hugging Face
·         Lab: RAG with PyTorch
·         Practice Quiz: Module 1: RAG Framework
·         Reading:Summary and Highlights 
·         Graded Quiz: RAG Framework

Module 2: Prompt Engineering and LangChain

·         Reading: Module 2 Introduction and Learning Objectives
·         Video: Introduction to LangChain
·         Video: Introduction to In-context Learning
·         Video: Advanced Methods of Prompt Engineering
·         Lab: In-Context Engineering and Prompt Templates
·         Video: LangChain: Core Concepts
·         Video: LangChain Documents for Building RAG Applications
·         Video: LangChain Chains and Agents for Building Applications
·         Lab: LangChain
·         Lab: Guided Project: Summarize Private Documents Using RAG, LangChain, and LLMs
·         Practice Quiz: Prompt Engineering and LangChain
·         Reading: Summary and Highlights: Prompt Engineering and LangChain
·         Graded Quiz: Prompt Engineering and LangChain
·         Reading: Cheat Sheet: Fundamentals of Building AI Agents using RAG and LangChain
·         Reading: Glossary: Fundamentals of Building AI Agents using RAG and LangChain
·         Reading: Course Conclusion
·         Reading: Congratulations and Next Steps
·         Reading: Thanks from the Course Team
·         Reading: Copyrights and Trademarks

Recommended Skills Prior to Taking this Course

Basic knowledge of Generative AI, prompt engineering techniques, and working knowledge of machine learning with Python and PyTorch.  
 
To transition to a career in Generative AI fine-tuning transformers, we recommend you enroll in the full Professional Certificate program and work through the courses in order. Within a few months, you’ll have job-ready skills and practical experience on your resume that will catch an employer's eye! 

Instructors

IBM Skills Network Team

Administrator

IBM Skills Network

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