Curriculum

19 Chapters · 19 Lessons

  1. 1

    Book Preview

    1. Mastering Large Language Models with Python Free preview
  2. 2

    Introduction

    1. (Included in full purchase)

      Introduction

  3. 3

    Chapter 1 : The Basics of Large Language Models and Their Applications

    1. (Included in full purchase)

      The Basics of Large Language Models and Their Applications

  4. 4

    Chapter 2 : Demystifying Open-Source Large Language Models

    1. (Included in full purchase)

      Demystifying Open-Source Large Language Models

  5. 5

    Chapter 3 : Closed-Source Large Language Models

    1. (Included in full purchase)

      Closed-Source Large Language Models

  6. 6

    Chapter 4 : LLM APIs for Various Large Language Model Tasks

    1. (Included in full purchase)

      LLM APIs for Various Large Language Model Tasks

  7. 7

    Chapter 5 : Integrating Cohere API in Google Sheets

    1. (Included in full purchase)

      Integrating Cohere API in Google Sheets

  8. 8

    Chapter 6 : Dynamic Movie Recommendation Engine Using LLMs

    1. (Included in full purchase)

      Dynamic Movie Recommendation Engine Using LLMs

  9. 9

    Chapter 7 : Document-and Web-based QA Bots with Large Language Models

    1. (Included in full purchase)

      Document-and Web-based QA Bots with Large Language Models

  10. 10

    Chapter 8 : LLM Quantization Techniques and Implementation

    1. (Included in full purchase)

      LLM Quantization Techniques and Implementation

  11. 11

    Chapter 9 : Fine-Tuning and Evaluation of LLMs

    1. (Included in full purchase)

      Fine-Tuning and Evaluation of LLMs

  12. 12

    Chapter 10 : Recipes for Fine-Tuning and Evaluating LLMs

    1. (Included in full purchase)

      Recipes for Fine-Tuning and Evaluating LLMs

  13. 13

    Chapter 11 : LLMOps - Operationalizing LLMs at Scale

    1. (Included in full purchase)

      LLMOps - Operationalizing LLMs at Scale

  14. 14

    Chapter 12 : Implementing LLMOps in Practice Using MLflow on Databricks

    1. (Included in full purchase)

      Implementing LLMOps in Practice Using MLflow on Databricks

  15. 15

    Chapter 13 : Mastering the Art of Prompt Engineering

    1. (Included in full purchase)

      Mastering the Art of Prompt Engineering

  16. 16

    Chapter 14 : Prompt Engineering Essentials and Design Patterns

    1. (Included in full purchase)

      Prompt Engineering Essentials and Design Patterns

  17. 17

    Chapter 15 : Ethical Considerations and Regulatory Frameworks for LLMs

    1. (Included in full purchase)

      Ethical Considerations and Regulatory Frameworks for LLMs

  18. 18

    Chapter 16 : Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning)

    1. (Included in full purchase)

      Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning)

  19. 19

    INDEX

    1. (Included in full purchase)

      INDEX

About the course

“Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence.

About the Author

Raj Arun is a distinguished expert in Artificial Intelligence and Data Science, with over fifteen years of industry experience. He holds an MBA from the Indian Institute of Management, Tiruchirapalli, and specialized diplomas in blockchain technology from the Indian Institute of Technology in Madras and Guwahati. Raj is also certified as a quantum Qiskit developer from IBM, marking him as a versatile professional who bridges the gap between traditional computing and quantum advancements.