Introduction to scientific data analysis and visualization with Python 0800-SCIEDATA

The course will introduce students to using Python and interactive Jupyter Notebooks (https://docs.jupyter.org/en/latest/) to analyze and visualize different types of scientific data (e.g. data measured during laboratory work, or calculated based on various physical models).

Preliminary course schedule (computer laboratories):
1. Introduction: Types of scientific data
2. Introduction to Python and Jupyter Notebooks
3. Introduction to Python (continued): Numpy and Matplotlib
4. Visualizing one-variable functions
5. Visulizing one-variable functions (continued)
6. Visualizing two-variable functions
7. Visualizing two-variable functions (continued)
8. Visualizing multi-dimensional data: isosurfaces
9. Visualizing multi-dimensional data: band structure
10. Working with large datasets: Pandas
11. Working with large datasets: Pandas (continued)
12. Course projects
13. Statistical analysis
14. Estimation of errors
15. Project work