Course Curriculum

    1. Introduction

    2. Learning Objectives

    1. How Do Machines Learn?

    2. How Are Semantic Relationships Captured?

    3. Human vs. Machine Understanding

    1. Tokenization

    2. Decode Your Words

    3. Embeddings

    4. Tokens Vs. Embeddings

    5. Vector Databases

    6. What Are Large Language Models?

    7. Prompt Engineering

    8. From Tokens to Meaning

    1. Customizing LLMs

    2. Training Models from Scratch

    3. In-Context Learning

    4. Fine-Tuning Models

    5. Retrieval-Augmented Generation

    6. Customizing Large Language Models

    1. Expectations vs. Reality of AI Adoption

    2. Types of Challenges

    3. Human Behavior Challenges

    4. Business Challenges

    5. Prompting Challenges

    6. AI Governance and Security

    1. Understanding the LLM Landscape

    2. Key Challenges in Adoption of LLMs

About this course

  • Free
  • 29 lessons
  • 1.5 hours of video content