This two-day online course provides you with the fundamental skills needed to make quantitative analyses on various datasets. You’ll learn the basics of collecting your own data from the internet, cleaning and preprocessing it, and finally analyzing it based on your research questions.
What Is This Course About?
The first day of the workshop will cover Python basics. You will get an introduction of the Jupyter Notebook, essential modules, data types, operators, conditional statements,functions, loops, compound data types, and comprehensions used in Python. This session concludes with hands-on exercises. In the afternoon, you’ll learn webscraping with practical exercises.
The second day will focus on data analysis in social sciences using pandas with the Titanic dataset, creating visualizations using Matplotlib and Seaborn, and we’ll touch upon advanced techniques like principal component analysis, linear regression, and logistic regression.
After each day you can work on assignments, for which you can get detailed feedback by thetrainer.
Learning Goals
1. Understand and apply basic Python programming concepts, including data types,
operators, control flow, functions, loops, and data structures.
2. Use Jupyter Notebook as a coding and analysis environment for interactive
programming and documentation.
3. Perform web scraping to collect textual and structured data from websites using
Python libraries.
4. Clean, preprocess, and explore datasets using the pandas library, with an
emphasis on social science applications.
5. Create informative visualizations using Matplotlib and Seaborn to support data
exploration and analysis.
6. Apply basic statistical modeling techniques, including principal component analysis
(PCA), linear regression, and logistic regression, to analyze real-world datasets.
7. Formulate and investigate research questions using quantitative data, integrating
programming, data collection, and analysis techniques.
8. Receive and incorporate feedback on assignments to reinforce understanding and
improve practical skills.
Recommended Readings for the Course
None
Assignments for the Course
Daily assignments/homework (not graded, feedback provided).
Schedule
- 9:30-11.00: session 1 (asynchronous/synchronous)
- 11:00-11:30: break
- 11:30-13:00: session 2 (asynchronous/synchronous)
- 13:00-14.00: lunch break
- 14:00-15:00: session 3 (group work, Q&A)
Who Is Your Instructor?
Rebeka O’Szabo is an assistant professor at the Center for Collective Learning, Corvinus University of Budapest. She is the leader of the Organizational Dynamics Group. Rebeka holds a PhD in network science from the Central European University, and has a background in sociology. She has been researching organizational and team dynamics (in escape rooms). Rebeka’s main scientific interest covers social networks, teams, organizations, and applied social psychology.
Website: https://rebekaoszabo.wixstudio.com/rebekaoszabo/
Linkedin: https://www.linkedin.com/in/rebekaoszabo/
