Enhancing Your Notebook Workflow with Jupyter AI

1h 10mIntermediate2025-07-17

Authors

Wuraola Oyewusi

Wuraola Oyewusi is an experienced data scientist, machine learning, and artificial intelligence professional.

Course details

Get a comprehensive introduction to Jupyter AI, the powerful extension that integrates generative AI capabilities into the Jupyter ecosystem. Instructor Wuraola Oyewusi begins with an overview of foundational concepts, before showing you how to set up and configure your environment with various AI model providers. Through hands-on practical demonstrations, you'll master easy-to-use techniques for leveraging AI to generate, explain, refactor, and debug code. An ideal fit for data scientists, machine learning practitioners, and developers, this course concludes with a capstone project that reinforces and tests out your new skills.

Learning objectives
Configure and integrate AI models within JupyterLab environments using Jupyter AI.
Generate, explain, and optimize code using natural language prompts and AI assistance.
Apply Jupyter magic commands (%ai and %%ai) to interact directly with language models.
Create complete notebooks with AI assistance to solve data science problems.
Debug code and understand complex concepts with AI-powered explanations.

Skills covered

JupyterAI Productivity ToolsArtificial Intelligence FoundationsSoftware Development ToolsArtificial Intelligence for BusinessArtificial Intelligence (AI)Business Software and ToolsOpen SourceSoftware DevelopmentOne-Off

Concepts

0. Introduction

01 - Learning Jupyter AI
02 - What you should know

1. Introduction to AI in the Jupyter Ecosystem

03 - Notebooks as IDE in data science and machine learning
04 - The Jupyter ecosystem
05 - Generative AI for coding assistance
06 - What is Jupyter AI

2. Setting Up Your Jupyter AI Environment

07 - Launching and managing JupyterLab environments
08 - Jupyter AI model providers
09 - Launching JupyterLab and Jupyter AI in an Anaconda environment
10 - Setting up Jupyternaut and exploring JupyterLab interface

3. Using the Jupyter AI Chat Interface (Jupyternaut)

11 - Generating code snippets
12 - Explaining code and concepts
13 - Building contextual knowledge in Jupyter AI
14 - Generating full notebooks from prompts

4. Using Magic Commands for AI Assitance in Jupyter AI

15 - Intro to AI magic commands in notebooks
16 - Using AI magic commands in Jupyter AI

5. Final Project

17 - Challenge - Integrate Jupyter AI into notebook workflow
18 - Solution - Integrate Jupyter AI into notebook workflow

Conclusion

19 - Next steps on using AI in notebooks