Enroll Now!
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.