- Course name: Fundamentals of Python for Social Sciences and Public Management
- Theory hours: 16 hours
- Instructor: Alexander Quispe Rojas
- Teaching Assistant: Michael Encalada
This course covers the essential elements for developing programming skills with Python, with a focus on incorporating Python as a toolkit for quantitative research in the social sciences. The course emphasizes data handling and lays the foundation for training students in data science.
Students will learn basic programming concepts such as data structures, defining functions, and working with essential data analysis libraries, especially NumPy and Pandas.
This course is designed for students and professionals in the social sciences with no prior experience in programming languages, or those who have just started using statistical software such as Stata and are interested in working with data through code.
The main goal is to prepare students for the job market by providing a highly demanded skill that serves as preparation for an entry-level position or internship involving data science.
By the end of this course, students will be able to:
- Interact with Python through Jupyter Notebooks and use Markdown effectively.
- Write code to perform common data analysis tasks.
- Work autonomously with Python tools for data science in their research and professional roles.
- Introduction to Python 3.x and Markdown
- GitHub
- Basic Data Types
- Lists
- Dictionaries
- NumPy
- Pandas
Classes will be held synchronously via Zoom. The course will emphasize working with datasets relevant to the social sciences while exploring Python for data analysis.
The evaluation consists of three assignments, each contributing equally to the final grade.
| No. | Assessment Type | Weight (%) |
|---|---|---|
| 1 | Assignment 1 | 33.3% |
| 2 | Assignment 2 | 33.3% |
| 3 | Assignment 3 | 33.3% |