This data analysis project was part of my AI Engineering Master's program, for which I received a grade of 1.0. It examines the changes in the labor market due to technology and societal shifts, using training data from the Austrian Public Employment Service (AMS) from 2019 to 2023. The analysis focuses on demographic influences on the choice of vocational categories and the development of participant numbers in various vocational categories and labor market districts.
How do demographic factors such as gender and age group influence the choice of vocational category in AMS training programs, and how have participant numbers in various vocational categories and labor market districts developed from 2019 to 2023?
- A person's age group correlates with their vocational category.
- There are significant growth differences in the number of participants across various vocational categories, with expected growth in "Technical Occupations" and "Health, Teaching, and Cultural Occupations."
- The gender of participants is independent of the labor market district.
The following technologies and libraries were used for the analysis:
- Python
- Jupyter
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Plotly Express
- GeoPandas
- SciPy