Both Python and R are the de facto cornerstones of the modern data science working world. Python's data science modules offer a wide range of functions to evaluate data, analyze it statistically, visualize it and model it.
This course gives a short introduction to the Python programming language but focuses on data preparation, analysis and visualization. It covers typical approaches in the data science field, and participants learn how to plan and carry out a data science project and communicate it clearly to a broad audience. It also places particular emphasis on reproducible work and on how to store and organize your data in a future-proof way.
Topics
- Fundamentals and best practices of data management
- Data preparation and feature engineering
- Fundamentals of high-dimensional data analysis (e.g. distances and dimensionality reduction strategies)
- Data analysis and models with Python modules: numpy, pandas, scikit-learn
- Visualizations: interpreting data and communicating it clearly
Requirement: Some initial experience with Python, for example from our introductory Python course.