logo_toolbox2

Module 7: JupyterLab

In this module, you will learn about JupyterLab, one of the most popular development environments for data science projects.

0Module learning outcomes

1Jupyter notebooks

2✍️ Practice: Keeping a notebook

3Markdown for text formatting

4✍️ Practice: Markdown is everywhere we look

5Intermediate JupyterLab tips and tricks

6✍️ Practice: JupyterLab level up

7Advanced JupyterLab tips and tricks

8✍️ Practice: JupyterLab level up again

9What Did We Learn?

About this course

In this course, we will dive into the world of data science tools and utilities. While these tools are not strictly required for data analysis, they are necessary for maintaining efficient, reproducible, and collaborative workflows, and are essential building blocks for a successful and sustained data science career.

About the program

The University of British Columbia (UBC) is a comprehensive research-intensive university, consistently ranked among the 40 best universities in the world. The Key Capabilities in Data Science program was launched in September 2020 and is developed and taught by many of the same instructors as the UBC Master of Data Science program.