Jupyter & Notebooks for Data Science
Master Jupyter notebooks for exploratory analysis, prototyping, and reproducible research. Jupyter notebooks are the standard environment for data science and AI.
Level: Beginner · Category: Data Science · Estimated time: 4 hours
Prerequisites
- Python for AI
Lessons
- Jupyter Setup & Interface — Installing Jupyter, launching notebooks, and the interface overview.
- Cells, Kernels & Execution — Code cells, markdown cells, kernel management, and execution order.
- Magic Commands & Shortcuts — %timeit, %matplotlib, %%writefile, and keyboard shortcuts.
- Data Visualization in Notebooks — Matplotlib, Seaborn, Plotly inline, and interactive plots.
- Best Practices & Reproducibility — Clear outputs, deterministic execution, and version control.
- Extensions & Debugging — JupyterLab, extensions, and debugging with ipdb.
Topics covered
jupyter, notebooks, python, data-science, reproducibility