Usage of Python Language 2400-ZEWW842

Course Outline:

Overview of Python applications: data acquisition, analysis, and visualization
Web Scraping I: using the requests library for API queries; best practices for scraping
Web Scraping II: retrieving unstructured data independently using the Selenium library
Data Visualization I: using the Matplotlib library
Data Visualization II: creating charts with the Seaborn library
Data Visualization III: building interactive visualizations with Plotly
Data Visualization IV: developing interactive applications with Dash
Maps and Spatial Data: using Folium and GeoPandas
Introduction to Text Mining: working with text data, identifying keywords, analyzing frequency and co-occurrence
Introduction to Machine Learning: data preparation, ML pipeline, the sklearn package, and basic methods (decision trees, support vector machines)
Consultations on case study topic selection and methodology
Case study presentation applying a selected technique covered during the course (2 sessions)

Assessment:

The course is assessed through a team project. The project will focus on the use of Python for data analysis — for example, analyzing a selected social phenomenon based on an empirical study.

The classes will be based on materials prepared by the instructor as well as online sources.