Learn AI-Assisted Python Programming, Second Edition, Video Edition

Learn AI-Assisted Python Programming, Second Edition, Video Edition

by Leo Porter, Daniel Zingaro
Released October 2024
Publisher(s): Manning Publications
ISBN: None

Watch it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Video description

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

See how an AI assistant can bring your ideas to life immediately!

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.

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 Authors
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.

Quotes
..masterfully blends the basics of programming with the effective use of AI tools to produce code.
- Mehran Sahami, Stanford University

This is such a well thought out book from the point of view of someone just starting to code post generative AI tools.
- Ana Bell, MIT

You are about to learn programming with one of the most exciting human task-supporters of this century…
- From the foreword by Beth Simon, UC San Diego

This book accelerates your Copilot programming learning journey beyond what I ever thought possible.
- Austin Z. Henley, Microsoft

Table of contents

  1. Chapter 1. Introducing AI-assisted programming with GitHub Copilot
  2. Chapter 1. About the technology
  3. Chapter 1. How Copilot changes how we learn to program
  4. Chapter 1. What else can Copilot do for us?
  5. Chapter 1. Risks and challenges when using Copilot
  6. Chapter 1. The skills we need
  7. Chapter 1. Societal concerns about AI code assistants like Copilot
  8. Chapter 1. Summary
  9. Chapter 2. Getting started with Copilot
  10. Chapter 2. The software we’ll be using
  11. Chapter 2. Getting your system set up: Part 1
  12. Chapter 2. Working with Python in Visual Studio Code
  13. Chapter 2. Writing and running some small programs
  14. Chapter 2. Getting your system set up: Part 2
  15. Chapter 2. Addressing common Copilot challenges
  16. Chapter 2. Our path forward
  17. Chapter 2. Summary
  18. Chapter 3. Designing functions
  19. Chapter 3. The design cycle of functions with Copilot
  20. Chapter 3. Examples of creating good functions with Copilot
  21. Chapter 3. Benefits of functions
  22. Chapter 3. Roles of functions
  23. Chapter 3. What’s a reasonable task for a function?
  24. Chapter 3. Exercises
  25. Chapter 3. Summary
  26. Chapter 4. Reading Python code: Part 1
  27. Chapter 4. Asking Copilot to explain code
  28. Chapter 4. Top 10 programming features you need to know: Part 1
  29. Chapter 4. Exercises
  30. Chapter 4. Summary
  31. Chapter 5. Reading Python code: Part 2
  32. Chapter 5. Exercises
  33. Chapter 5. Summary
  34. Chapter 6. Testing and prompt engineering
  35. Chapter 6. Closed-box and open-box testing
  36. Chapter 6. How to test your code
  37. Chapter 6. Revisiting the cycle of designing functions with Copilot
  38. Chapter 6. Full testing example
  39. Chapter 6. Another full testing example: Testing with files
  40. Chapter 6. Exercises
  41. Chapter 6. Summary
  42. Chapter 7. Problem decomposition
  43. Chapter 7. Small examples of top-down design
  44. Chapter 7. Spelling suggestions
  45. Chapter 7. Spelling suggestions using top-down design
  46. Chapter 7. Breaking down the process subproblem
  47. Chapter 7. Summary of our top-down design
  48. Chapter 7. Implementing our functions
  49. Chapter 7. Exercises
  50. Chapter 7. Summary
  51. Chapter 8. Debugging and better understanding your code
  52. Chapter 8. How to find the bug
  53. Chapter 8. How to fix a bug (once found)
  54. Chapter 8. Modifying our workflow in light of our new skills
  55. Chapter 8. Applying our debugging skills to a new problem
  56. Chapter 8. Using the debugger to better understand code
  57. Chapter 8. A caution about debugging
  58. Chapter 8. Exercises
  59. Chapter 8. Summary
  60. Chapter 9. Automating tedious tasks
  61. Chapter 9. How to use Copilot to write tools
  62. Chapter 9. Example 1: Cleaning up email text
  63. Chapter 9. Example 2: Adding cover pages to PDF files
  64. Chapter 9. Example 3: Merging phone picture libraries
  65. Chapter 9. Exercises
  66. Chapter 9. Summary
  67. Chapter 10. Making some games
  68. Chapter 10. Adding randomness
  69. Chapter 10. Example 1: Bulls and Cows
  70. Chapter 10. Example 2: Bogart
  71. Chapter 10. Exercises
  72. Chapter 10. Summary
  73. Chapter 11. Creating an authorship identification program
  74. Chapter 11. Authorship identification using top-down design
  75. Chapter 11. Breaking down the process subproblem
  76. Chapter 11. Summary of our top-down design
  77. Chapter 11. Implementing our functions
  78. Chapter 11. Going further
  79. Chapter 11. Exercises
  80. Chapter 11. Summary
  81. Chapter 12. Future directions
  82. Chapter 12. Limitations and future directions
  83. Chapter 12. Exercises
  84. Chapter 12. Summary

Product information

  • Title: Learn AI-Assisted Python Programming, Second Edition, Video Edition
  • Author(s): Leo Porter, Daniel Zingaro
  • Release date: October 2024
  • Publisher(s): Manning Publications
  • ISBN: None