Quick Guide & Tips

đŸ’»   Accessing Utils File and Helper Functions

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.

đŸ’»   Downloading Notebooks

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Download as"

3:   Then, click on "Notebook (.ipynb)"

đŸ’»   Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.

📗   See Your Progress

Once you enroll in this course—or any other short course on the DeepLearning.AI platform—and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).

đŸ“±   Features to Use

🎞   Adjust Video Speed: Click on the gear icon (⚙) on the video and then from the Speed option, choose your desired video speed.

🗣   Captions (English and Spanish): Click on the gear icon (⚙) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

🔅   Video Quality: If you do not have access to high-speed internet, click on the gear icon (⚙) on the video and then from Quality, choose the quality that works the best for your Internet speed.

đŸ–„   Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

√   Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.

🧑   Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

🧑   Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

📅   Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

☕   Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

💬   Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

✍   Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.

📚   Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. 👇

👉👉 🔗 DeepLearning.AI – All Short Courses [+]

🙂   Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community 👉👉 🔗 DeepLearning.AI Forum

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Welcome back!

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We'd like to know you better so we can create more relevant courses. What do you do for work?

DeepLearning.AI
Short CourseBeginner

Jupyter AI: AI Coding in Notebooks

Instructors: Andrew Ng, Brian Granger

Project Jupyter logo
  • Beginner
  • 5 Video Lessons
  • 3 Code Examples
  • Instructors: Andrew Ng, Brian Granger
    • Project Jupyter
    Project Jupyter

What you'll learn

  • Use Jupyter AI to generate code, debug errors, and get explanations—all without leaving your notebook environment.

  • Build AI applications from scratch, including a book research assistant and a stock data analysis workflow, using Jupyter AI.

  • Apply AI coding best practices to guide Jupyter AI with the right context to successfully build your projects.

About this course

Learn to use Jupyter AI as your notebook coding partner in this short course, taught by Andrew Ng and Brian Granger, co-founder of Project Jupyter.

Coding practices are shifting from manual coding to AI-assisted development, and Jupyter AI allows you to integrate AI coding into all your notebook development workflows. Many AI coding assistants struggle to function well within the notebook environment, the Project Jupyter team has introduced Jupyter AI, which is an open-source framework that deeply integrates AI coding and collaboration into Jupyter notebooks and JupyterLab.

Jupyter AI provides a chat interface that you can use to generate new cells in your notebook. You can also drag existing cells into the chat for debugging, attach files for context, and save chat histories to reuse later as additional context for your work.

In this course, you’ll build a book research assistant using the Open Library API, and create a stock market data analysis workflow, all with the help of Jupyter AI. You’ll learn how to provide API documentation as context so the LLM generates accurate syntax for code that wasn’t part of its pretraining.

In detail, you’ll use Jupyter AI to:

  • Generate, refactor and explain code, including making API calls to services like OpenAI and performing statistical data analysis.
  • Build a book research assistant using the Open Library API by providing Jupyter AI with the API documentation as context.
  • Create a stock market data analysis workflow that you can use to perform analysis and visualization of financial data.

This course offers an early look at how Jupyter AI is reshaping coding in notebooks—and how you can start using it today!

Whether you’re a data scientist, AI developer, educator, or new to coding and you want to leverage AI coding assistance, this course gives you hands-on experience with a framework designed specifically for working with Jupyter notebooks.

Who should join?

Any AI builder who wants to learn AI-assisted coding in Jupyter notebooks. No prior experience with AI coding tools required. Basic familiarity with Python is helpful.

Course Outline

5 Lessons・3 Code Examples

  • Introduction

    Video・4 mins

  • Coding with Jupyter AI

    Video・7 mins

  • Exercise 1

    Code Example・10 mins

  • Building an AI Book Research Assistant

    Video・9 mins

  • Exercise 2

    Code Example・10 mins

  • Exploring Stock Market Data

    Video・8 mins

  • Exercise 3

    Code Example・10 mins

  • How to Set Up Jupyter AI Locally

    Reading・3 mins

  • Conclusion

    Video・1 min

  • Quiz

    Graded・Quiz

    ・9 mins

Instructors

Andrew Ng

Andrew Ng

Founder, DeepLearning.AI; Co-founder, Coursera

Brian Granger

Brian Granger

Course access is free for a limited time during the DeepLearning.AI learning platform beta!

Want to learn more about Generative AI?

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