RAG Skills you will learn

  • RAG Basics
  • RAG Architecture Design
  • Transformer Architecture
  • Contextual Understanding
  • Dynamic Conversation Management

Who should learn this free RAG course?

  • AI Developer
  • Data Scientist
  • Machine Learning Engineer
  • NLP Specialist
  • Conversational AI Engineer

What you will learn in this free RAG course?

  • RAG Course for Beginners

    • Introduction

      01:34
      • Introduction
        01:34

    • Lesson 1: RAG Architecture

      32:34
      • RAG Architecture
        32:34

    • Lesson 2: RAG Architecture Coding Demonstration

      46:49
      • RAG Architecture Coding Demonstration
        46:49

    • Lesson 3: Transformer Models in NLP

      33:13
      • Transformer Models in NLP
        33:13

    • Lesson 4: Transformer Architecture with Self-attention

      53:42
      • Transformer Architecture with Self-attention
        53:42
About the Course

This RAG course introduces you to Retrieval-Augmented Generation (RAG), a cutting-edge technique combining information retrieval with generative AI to create accurate, context-aware outputs. Learn the fundamentals of RAG, explore its tools and workflows, and gain hands-on experience in building RAG-powered AI solutions. Designed for beginners, this course equips you with the skills to leverage RAG in solving real-world challenges.

Topics Covered:

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Why you should learn RAG?

$503.40 Billion

Expected size of global Machine Learning market by 2030.

$161K+ (USA) | INR 10 LPA

Average Salary of an ML Engineer annually.

FAQs

  • What is the RAG course for beginners about?

    This course introduces Retrieval-Augmented Generation (RAG), a method combining information retrieval and generative AI to create accurate, context-aware outputs.

  • Who should take this RAG Basics course?

    It’s ideal for beginners, AI enthusiasts, data scientists, and developers interested in exploring advanced AI techniques.

  • Do I need prior AI knowledge to enroll in this course?

    Basic understanding of programming and AI concepts is recommended, but the course is designed to be beginner-friendly.

  • What tools will I learn in this introduction to RAG course?

    You’ll work with tools like LangChain, Hugging Face, and vector databases to build RAG-powered applications.

  • What are the key topics covered?

    Topics include RAG fundamentals, memory in conversations, contextual prompts, building dynamic pipelines, and hands-on RAG application development.

  • Will I get hands-on experience in this course?

    Yes, the course includes practical exercises and projects to help you implement RAG systems and concepts.

  • How long does it take to complete the RAG Basics course?

    This RAG Course for beginners is 3 hours long.

  • What career opportunities does this course lead to?

    This course prepares you for roles like AI Developer, NLP Specialist, Data Scientist, and Conversational AI Engineer.

  • Will I earn a certificate after completing the RAG Basics course?

    Yes, upon successful completion, you will receive a certificate to validate your RAG knowledge and skills.

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  • Career Impact Results vary based on experience and numerous factors.