Main repository for the Python class at FU Berlin, summer semester 2024

Dates, location and outline of the class are presented here. Starts at 14:00 and ends at 18:00 CET

Content

• 01 - 2024/04/26

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

• 02 - 2024/05/03

  • Python 101

• 03 - 2024/05/10

  • Python 101 continued
  • Plotting with Python

• 04 - 2024/05/17

  • Introduction to pandas
  • Simple data analysis using pandas

• 05 - 2024/05/24

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

• 06 - 2024/05/31

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

• 07 - 2024/06/07

  • Study project - Powerplants (Group Session)

• 08 - 2024/06/14

  • Object Oriented Programming (OOP)
  • (Submission deadline: 2024/06/17)

• 09 - 2024/06/21

  • Presentations study projects

• 10 - 2024/06/28

  • Interpolation and curve fitting
  • Inferential statistics
  • Population vs. sample statistics
  • Central Limit Theorem
  • Point and interval estimates (confidence intervals)
  • Hypothesis testing
  • Bootstrapping
  • Introduction to Machine Learning
  • Skipped:
    • Regression analysis
    • Logistic regression
    • Hyperparameter tuning
    • Polynomial Regression

• 11 - 2024/07/05

  • Spyder IDE
  • Dashboarding with streamlit
  • Creating dynamic Maps with folium

• 12 - 2024/07/12

  • Web scraping
  • Wordclouds

• 13 - 2024/07/19

  • Feedback round
  • APIs (FastAPI)

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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 (Windows users: please use the Anaconda Powershell Prompt). You activate your new environment by typing

conda activate fupy

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.

(Note that this link points to the master branch)

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We should mention that the conda environments created during this course will take up a lot of space! Feel free to run conda env list to display all created environments and delete them if you choose using conda env remove -n env_name. Remember that you can always recreate any of the environments using conda env create -f environment.yml in any given sub- or the root-directory of this repo.