Advanced Methods | Introduction to Python Programming - Advanced Methods | PAIR

Knowledge

This course does not require prior programming experience. Basic computer literacy and an interest in quantitative or data-driven work are sufficient.

Description

This course provides a practical introduction to Python programming as a tool for data analysis, automation, and problem-solving. Students learn core programming concepts such as variables, control flow, functions, data structures, input/output, and modular programming. The course emphasizes good programming practices, reproducibility, and the use of Python in applied fields such as policy analysis, cultural analytics, and administrative research. Interactive exercises and short projects allow participants to translate conceptual understanding into practical coding competence using Jupyter notebooks or Google Colab.

Learning objectives

Students who successfully complete this course will be able to:

• Understand the basic structure and syntax of the Python programming language.
• Write, debug, and execute Python scripts for automating simple analytical tasks.
• Manipulate and visualize data using libraries such as 'pandas'and 'matplotlib'.
• Apply programming concepts to real-world domains.
• Collaborate effectively in data-driven projects using reproducible coding workflows.

E-learning

All course materials, lecture notebooks, and assignments will be made available through ILIAS.
Practical exercises will be implemented using Jupyter Notebooks or Google Colab.

Preparation

No explicit preparation is required. Introductory readings, python tutorials and optional video tutorials will be provided in the first session for students new to programming.

Detailed information about the examinations

Students are assessed through short in-class coding exercises and a final mini-project that showcases applied Python skills (loops, functions, pandas, visualization). The project includes a final report with discussion of the approach, implementation, and results.

Second additional field

Language of the course: English

Building Blocks of the Course:

• Python Basics: Syntax, Variables, and Data Types
• Flow Control and Functions
• Working with Data Structures (Lists, Dictionaries, Sets)
• Files, Input/Output, and Data Wrangling
• Introduction to Libraries for Data Analysis (pandas, numpy)
• Data Visualization and Communication of Results