Fundamentals of AI Agents Using RAG and LangChain

This course is part of multiple programs. Learn more

Instructors: Joseph Santarcangelo +3 more

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What you'll learn

  •   In-demand, job-ready skills businesses seek for building AI agents using RAG and LangChain in just 8 hours
  •   How tapply the fundamentals of in-context learning and advanced prompt engineering timprove prompt design
  •   Key LangChain concepts, including tools, components, chat models, chains, and agents
  •   How tbuild AI applications by integrating RAG, PyTorch, Hugging Face, LLMs, and LangChain technologies
  • Skills you'll gain

  •   Prompt Engineering
  •   OpenAI
  •   ChatGPT
  •   Artificial Intelligence
  •   Natural Language Processing
  •   Artificial Intelligence and Machine Learning (AI/ML)
  •   Generative AI
  •   Generative AI Agents
  •   Large Language Modeling
  • There are 2 modules in this course

    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!

    Prompt Engineering and LangChain

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