This is a collection of projects I did for the Udacity Data Analyst Nanodegree. Not all code is my own code.
This project was the first one, the goal was to learn basic data analysis skills.
Here, I downloaded Openstreetmap data, brought it into good form and performed an analysis to look for various factors. Documentation can be found in the Jupyter Notebook.
This is a short demonstration od inferential statistics at the example of Stroop Effect measurements.
This folder consists of many mini-projects used to get a better understanding of machine learning algorithms and principles. Some of the code was provided, I had to complete it according to the tasks. The original starter code was written in Python 2.7, I updated it to Python 3. There was a bigger project to demonstrate the learnings to be found in the folder 'final-project'. The Markdown file documents the process.