Advanced Data Science Tools in CodeGrade

Overcome challenges in your course

Complex workflows feel overwhelming: Students juggle data cleaning, feature engineering, and model training across multiple frameworks.

The “it worked on my machine” issue: Library mismatches can derail collaboration and debugging.

Evaluating advanced models requires nuanced feedback: Students need guidance on larger projects.

1. Streamline your workflow

Coordinating each step of a data science project shouldn’t mean toggling between tools. CodeGrade brings everything into one flow so students focus on insights, not installs.

Run and grade Jupyter Notebooks, Python/R scripts, and SQL queries in a single platform
Preconfigured, cloud‑based environments with popular libraries
Launch long‑running jobs in the cloud without overloading local machines

2. Keep everyone working together

Nothing derails a lesson faster than environment mismatches. Give every student the same setup and teach them reproducible practices that mirror industry.

Browser‑based IDE that eliminates dependency conflicts
GitHub/GitLab integration for real-world practice
Shared starter templates to jump‑start assignments

3. Deliver deep, timely feedback

Advanced projects deserve detailed guidance, and students need it while the work is fresh. CodeGrade lets you provide rich, targeted feedback without added hours.