Teach Data Science with CodeGrade

Overcome challenges in your course

Managing Jupyter Notebooks is inefficient: Sharing, collecting, and grading notebooks across platforms adds friction and consumes valuable teaching time.

Feedback doesn’t scale well: Large classes mean students wait for guidance and can disengage before they improve.

Students often have no coding background: Many struggle with R or Python syntax, debugging, or even using an IDE for the first time.

1. Simplify Jupyter from start to finish

Delegate managing to CodeGrade while you focus on teaching. You can assign, run, and grade notebooks all in one place.

Launch Jupyter Notebooks directly in the browser
Distribute and collect work through your LMS
Automatically ensure every student has the right environment
No setup required—students can start analyzing data right away

2. Give meaningful feedback without the time cost

Teaching analysis and code takes time, especially when answers aren’t one-size-fits-all. CodeGrade helps you scale personalized feedback without burning out.

Autograde notebooks and scripts in just a few clicks
Provide inline comments on student code or plots
Reusable feedback snippets make grading consistent and fast
Students can resubmit after feedback to close the learning loop

3. Make coding accessible to all

Many students in data science are new to programming. CodeGrade removes tech barriers so they can focus on learning analysis, not fighting their tools.