Data Competency: Data Visualization and Statistics with Python

You have first experiences with R, but you'd like to use Python for your data visualization and statistical analyses in the future? You have used a bit of Python in the past and now you'd like to explore the capabilities of Python for data visualization and statistics? You would like to create better looking graphs and plots in Python? If you've answered one or more of the questions above with "yes", you should participate in this course.

This course intends to introduce the course participants to the capabilities of Python for data visualization and statistical analyses using the popular libraries matplotlib, seaborn, pandas, statsmodels and sklearn. The course language will be English. Jupyter Notebooks, a popular, interactive environment for Python, will be used throughout this course. Some prior knowledge in Python or R would be beneficial.

The participants will be introduced in particular during two sessions of 4h each to

  • data Visualization (various two- and three-dimensional plot types)

  • descriptive Statistics

  • statistical Tests (Chi-Square, T-Test)

  • correlation

  • regression

To allow the participants to study the material afterwards in their own pace, the Jupyter Notebooks will contain links to short explanatory videos for each step in the sessions.