Course curriculum

    1. Course Intro

    2. Introduction to the Instructor

    3. Introduction to Gen AI

    4. Benchmark Assessment

    5. What are LLMs?

    6. How do LLMs work?

    7. How do you use Gen AI on your workflow?

    1. Large Language Models

    2. Practical uses of LLMs

    3. Types of models

    4. Pricing models for LLMs

    1. Prompt Engineering Basics

    2. Prompt Engineering Techniques

    3. Chain of Thought Processing

    4. Rule of Thumb When Crafting a Prompt

    1. RAG

    2. Rag Use Cases

    3. Agents

    4. Use Cases of Different LLMs

    5. Rag Pipeline

    6. AI Agents

    7. AI Agent Tools and Autonomy

    8. Recap of AI Agents

    9. Recap of Indexing

    1. Challenges in Implementing RAG Systems

    2. Why relevant context matters for LLMs

    3. LLM Embeddings and Vectors

    4. Chunking

    5. Fine-Tuning

    6. Challenges and Draw Backs

    7. Bias in LLM

    8. Ethics in LLMs

    9. LLM Regulations

    10. AGI

    1. AI Development vs Traditional Development

    2. Developing and Launching and AI Products

    3. Metrics for Evaluating AI Systems

    4. The Critical Role of AI

    5. AI Assisted Testing and the Development Life Cycle

About this course

  • Free
  • 40 lessons
  • 1.5 hours of video content

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