README.md

DEC's Python for Data Science

This repository contains all the material for the DEC Python training. This training is developed by DIME and DECID.

Course content

This training is structured into three parts. Part 0 is a single-session introduction for people with no coding background. Part 1 is a course that covers the foundations of Python used in almost any type of Python data science project. Part 2 is a collection of stand-alone sessions that assumes knowledge in the foundations of Python and each session dives deeper into the advanced topic.

Links to content

• Part 0 - Intro to Programming
  • Slides
• Part 1 - Foundations of Data Science in Python
  • Session 1 - Variable types and Python syntax
    • Jupyter notebook
    • Colab notebook
    • Suggested solutions
  • Session 2 - Control flow and functions
    • Jupyter notebook
    • Colab notebook
    • Suggested solutions
  • Session 3 - NumPy and Pandas
    • Jupyter notebook
    • Colab notebook
    • Suggested solutions
  • Session 4 - APIs and introduction to data visualization in Python
    • APIs
      • Slides
      • Jupyter notebook
      • Colab notebook
      • Suggested solutions
    • Data visualization
      • Jupyter notebook
      • Colab notebook
  • Project 1 - Schelling model
    • Jupyter notebook
    • Colab notebook
    • Suggested solutions
  • Project 2 - Raster data analysis and ML inference
    • Jupyter notebook
    • Colab notebook
    • Suggested solutions
• Part 2 - Advanced topics of Data Science of Python
  • Geospatial analysis
    • Jupyter notebook
    • Colab notebook
  • Introduction to text analysis
    • Jupyter notebook
    • Colab notebook
  • Introduction to data pipelines
    • Introduction to data pipelines - Jupyter notebook
    • Other session materials

Contact

If you have any questions you can contact one of the teams behind this training on [email protected].