Dates, location and outline of the class are presented here. Starts at 13:15 to 16:30 CET

• 01 - 2020/11/06

  • Introduction into computational thinking
  • Programming languages and IDEs
  • Why Python?

• 02 - 2020/11/13

  • Python 101

• 03 - 2020/11/20

  • Python 101 continued
  • Plotting with Python
  • Introduction to pandas

• 04 - 2020/11/27

  • Pandas recap
  • Simple data analysis using pandas
  • Reporting using nbsphinx

• 05 - 2020/12/04

  • Exploratory data analysis (EDA)
  • Study project - WW2

• 06 - 2020/12/18

  • Interpolation and curve fitting
  • Inferential statistics
  • Population vs. sample statistics

• 07 - 2020/01/08

  • Presentations study projects

• 08 - 2021/01/15

  • Presentations study projects

• 09 - 2021/01/22

  • Basics of git
  • Central Limit Theorem
  • Point and interval estimates (confidence intervals)
  • bootstrapping
  • Hypothesis testing

• 10 - 2021/01/29

  • Introduction to Machine Learning
  • Regression analysis
  • Scikit Learn
  • Logisitic regression
  • Hyperparamter tuning

• 11 - 2021/02/05

  • Polynomial Regression
  • Spyder IDE
  • Object oriented programming - Python classes

• 12 - 2021/02/12

  • Web scraping
  • Wrap-up

In order to re-run the class materials I encourage you to use the conda package manager. Once installed, create an environment and install all required dependencies on your machine by typing

conda env create -f environment.yml

into your console. You activate your new environment by typing

source activate fupy (on LINUX and Mac) or

activate fupy (on WINDOWS).

Then you are ready to go (if you are stuck check out the conda documentation site). Alternatively, you may launch binder to get a reproducible executable environment immediately in your browser. Simply click the launch binder icon below.