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SciPyCourse2019

Introduction to Scientific Programming in Python, LMU, 2019

12 classes on Tuesdays, April 30 to July 16, 2019
LMU Biozentrum, Room C00.013
13-15:30, 3 ECTS total

Taught by Martin Spacek

Class notes and files: https://github.com/SciPyCourse2019/notes

Description

Introduction to the Python programming language, with a focus on practical tools and techniques for scientific data analysis. Previous programming experience in a language such as Matlab or R is an asset, but not required. Introduces various key Python libraries, and provides example problems. Students will be encouraged to bring their own specific data analysis problems to class, for immediate applicability to their work, culminating in a course project. Basic command line operations and code version control with Git will also be covered. Students are expected to bring their own laptop. A minimal level of attendance (9/12 classes) and participation is required, and minimal homework exercises will be assigned.

This is course no. 19322 in the official course listing.

Class outline

  1. Python basics
  2. Python basics 2
  3. collections
  4. numpy 1D arrays
  5. numpy data types
  6. numpy file operations, plotting with matplotlib
  7. more matplotlib, matrices
  8. image analysis
  9. data analysis with Pandas
  10. statistics
  11. organizing code, data, results; version control with Git; work on project
  12. options:
    • review
    • dimension reduction & clustering
    • hierarchical indexing in pandas
    • work on project

Class project

Here are the class project guidelines.

Tutorials

These are all free, and require no signup or login:

Basic Python

IPython and Jupyter

Specific libraries

Cheat sheets