Mastering ChatGPT: Free Course by AI Guru Andrew Ng

Mastering ChatGPT: Free Course by AI Guru Andrew Ng

Table of Contents:

1. Introduction
2. The Power of Large Language Models for Developers
3. Best Practices for Prompting in Software Development
4. Common Use Cases for Large Language Models
   • Summarizing
   • Inferring
   • Transforming
   • Expanding
5. Building a Chatbot with a Large Language Model
6. Base Language Models vs. Instruction-Tuned Language Models
7. Practical Applications of Instruction-Tuned Language Models
8. Acknowledgments
9. Tips for Giving Clear and Specific Instructions
10. Giving Language Models Time to Think

Introduction

Welcome to this course on using Chat GPT as a tool for engineering and development. In this course, we will explore the power of large language models and share best practices for using them effectively in software development. You will learn how to build applications using API calls to these models and discover various use cases for implementing them.

The Power of Large Language Models for Developers

Large language models have transformed the way developers approach software development. While many resources focus on using the Chat GPT web user interface for specific tasks, this course aims to Show you the potential of these models for quick software application development through API calls. We will explore the possibilities offered by large language models and provide you with best practices for maximizing their potential.

Best Practices for Prompting in Software Development

In this section, we will cover the best practices for effectively prompting large language models in software development. Prompting is crucial to guide the models in generating the desired output. By following these best practices, you can ensure more accurate and Relevant responses.

Common Use Cases for Large Language Models

Large language models can be utilized in various use cases. We will Delve into common scenarios such as summarizing text, inferring information, transforming data, and expanding on existing content. Each use case will be explored in Detail, providing you with practical examples and guidance for implementing them.

Building a Chatbot with a Large Language Model

One of the exciting applications of large language models is building chatbots. In this section, you will learn how to Create a chatbot using a large language model. Step-by-step instructions will be provided, along with tips and tricks for improving the chatbot's performance.

Base Language Models vs. Instruction-Tuned Language Models

There are two main types of large language models: base language models and instruction-tuned language models. In this section, we will discuss the differences between these models and when to use each one. Understanding these distinctions will help you choose the most suitable model for your specific development needs.

Practical Applications of Instruction-Tuned Language Models

Instruction-tuned language models have gained significant Momentum in research and practice. This section will explore practical applications for instruction-tuned language models. You will discover how these models can be easily integrated into your applications, making them more helpful, honest, and aligned with your requirements.

Acknowledgments

We would like to express our gratitude to the teams from OpenAI and Deep Learning.ai for their contributions to the material presented in this course. Their expertise and collaboration have been invaluable in shaping the curriculum and ensuring the quality of the course content.

Tips for Giving Clear and Specific Instructions

When working with instruction-tuned language models, providing clear and specific instructions is crucial. This section will provide you with tips and techniques for effectively conveying your requirements to the model. By following these guidelines, you can enhance the model's understanding and generate more accurate output.

Giving Language Models Time to Think

Allowing language models sufficient time to think and process information is essential for obtaining optimal results. This section will explain why giving models time to think is important and provide strategies to optimize the model's thinking process. By employing these techniques, you can enhance the model's performance and achieve more accurate and insightful responses.

Building Applications with Large Language Models

Welcome to this course on using Chat GPT for software development. In this course, we will explore how large language models can revolutionize the way developers create applications. Large language models offer tremendous potential as a tool for quickly building software using API calls. We will cover best practices for prompting these models effectively and explore common use cases such as summarizing text, inferring information, transforming data, and expanding content.

One of the most exciting applications of large language models is the creation of chatbots. In this course, you will learn how to build a chatbot using a large language model, step-by-step. We will also discuss the differences between base language models and instruction-tuned language models, providing insights into when to use each one.

Throughout the course, we will emphasize practical applications and share tips for giving clear and specific instructions, ensuring the desired output from the language models. Additionally, we will highlight the importance of allowing the models sufficient time to think, optimizing their performance and generating more accurate responses.

By the end of this course, you will have a comprehensive understanding of how to leverage large language models in your software development projects. Join us as we embark on this exciting Journey through the world of large language models and discover their limitless potential.