Whether you know Python or not, this book will help you write amazing Python code using the latest versions of Copilot or ChatGPT.

Once, to be a programmer you had to write every line of code yourself. Now tools like GitHub Copilot can instantly generate working programs based on your description in plain English. An instant bestseller, Learn AI-Assisted Python Programming has taught thousands of aspiring programmers how to write Python the easy way—with the help of AI. It’s perfect for beginners, or anyone who’s struggled with the steep learning curve of traditional programming.

In Learn AI-Assisted Python Programming, Second Edition you’ll learn how to:

• Write fun and useful Python applications—no programming experience required!
• Use the GitHub Copilot AI coding assistant to create Python programs
• Write prompts that tell Copilot exactly what to do
• Read Python code and understand what it does
• Test your programs to make sure they work the way you want them to
• Fix code with prompt engineering or human tweaks
• Apply Python creatively to help out on the job

AI moves fast, and so the new edition of Learn AI-Assisted Python Programming, Second Edition is fully updated to take advantage of the latest models and AI coding tools. Written by two esteemed computer science university professors, it teaches you everything you need to start programming Python in an AI-first world. You’ll learn skills you can use to create working apps for data analysis, automating tedious tasks, and even video games. Plus, in this new edition, you’ll find groundbreaking techniques for breaking down big software projects into smaller tasks AI can easily achieve.

Foreword by Beth Simon.

About the technology

The way people write computer programs has changed forever. Using GitHub Copilot, you describe in plain English what you want your program to do, and the AI generates it instantly.

About the book

This book shows you how to create and improve Python programs using AI—even if you’ve never written a line of computer code before. Spend less time on the slow, low-level programming details and instead learn how an AI assistant can bring your ideas to life immediately. As you go, you’ll even learn enough of the Python language to understand and improve what your AI assistant creates.

What''s inside

• Prompts for working code
• Tweak code manually and with AI help
• AI-test your programs
• Let AI handle tedious details

About the reader

If you can move files around on your computer and install new programs, you can learn to write useful software!

About the author

Dr. Leo Porter is a Teaching Professor at UC San Diego. Dr. Daniel Zingaro is an Associate Teaching Professor at the University of Toronto.

The technical editor on this book was Peter Morgan.

Table of Contents

1 Introducing AI-assisted programming with GitHub Copilot
2 Getting started with Copilot
3 Designing functions
4 Reading Python code: Part 1
5 Reading Python code: Part 2
6 Testing and prompt engineering
7 Problem decomposition
8 Debugging and better understanding your code
9 Automating tedious tasks
10 Making some games
11 Creating an authorship identification program
12 Future directions

Whether you know Python or not, this book will help you write amazing Python code using the latest versions of Copilot or ChatGPT.

Once, to be a programmer you had to write every line of code yourself. Now tools like GitHub Copilot can instantly generate working programs based on your description in plain English. An instant bestseller, Learn AI-Assisted Python Programming has taught thousands of aspiring programmers how to write Python the easy way—with the help of AI. It’s perfect for beginners, or anyone who’s struggled with the steep learning curve of traditional programming.

In Learn AI-Assisted Python Programming, Second Edition you’ll learn how to:

• Write fun and useful Python applications—no programming experience required!
• Use the GitHub Copilot AI coding assistant to create Python programs
• Write prompts that tell Copilot exactly what to do
• Read Python code and understand what it does
• Test your programs to make sure they work the way you want them to
• Fix code with prompt engineering or human tweaks
• Apply Python creatively to help out on the job

AI moves fast, and so the new edition of Learn AI-Assisted Python Programming, Second Edition is fully updated to take advantage of the latest models and AI coding tools. Written by two esteemed computer science university professors, it teaches you everything you need to start programming Python in an AI-first world. You’ll learn skills you can use to create working apps for data analysis, automating tedious tasks, and even video games. Plus, in this new edition, you’ll find groundbreaking techniques for breaking down big software projects into smaller tasks AI can easily achieve.

Foreword by Beth Simon.

About the technology

The way people write computer programs has changed forever. Using GitHub Copilot, you describe in plain English what you want your program to do, and the AI generates it instantly.

About the book

This book shows you how to create and improve Python programs using AI—even if you’ve never written a line of computer code before. Spend less time on the slow, low-level programming details and instead learn how an AI assistant can bring your ideas to life immediately. As you go, you’ll even learn enough of the Python language to understand and improve what your AI assistant creates.

What''s inside

• Prompts for working code
• Tweak code manually and with AI help
• AI-test your programs
• Let AI handle tedious details

About the reader

If you can move files around on your computer and install new programs, you can learn to write useful software!

About the author

Dr. Leo Porter is a Teaching Professor at UC San Diego. Dr. Daniel Zingaro is an Associate Teaching Professor at the University of Toronto.

The technical editor on this book was Peter Morgan.

Table of Contents

1 Introducing AI-assisted programming with GitHub Copilot
2 Getting started with Copilot
3 Designing functions
4 Reading Python code: Part 1
5 Reading Python code: Part 2
6 Testing and prompt engineering
7 Problem decomposition
8 Debugging and better understanding your code
9 Automating tedious tasks
10 Making some games
11 Creating an authorship identification program
12 Future directions