Python Programming

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент политологии и международных отношений

Статус:

Курс обязательный

Когда читается:

1-й курс, 1, 2 модуль

Преподаватель

Барыкин Ярослав Андреевич

Course Syllabus

Abstract

This course aims to teach students the basics of programming in Python and to demonstrate how coding can be used for practical and academic purposes. Upon completion, students are expected to understand the theoretical basis of Python programming, execute simple scripts, and process data using the Jupyter IDE with packages like pandas.

Learning Objectives

• • To give students a comprehensive overview of the Python programming language
• • To develop basic skills of programming in Python
• • To develop skills of processing data using Python packages

Expected Learning Outcomes

• knows primary data types, operations with them and basic programming constructs
• writes and executes simple scripts
• knows how to process data using imported packages

Course Contents

• 1. Introduction to Python. Jupyter IDE and. ipynb format
• 2. Basic data types and operations with them
• 3. Sequences, sets, dictionaries and operations with them
• 4. Conditional statements
• 5. Loops and exceptions
• 6. Functions
• 7. Processing data using Pandas
• 8. Processing and visualizing data with Numpy and Matplotlib

Assessment Elements

• Final project
  A project requires students to look for a data source and conduct its preliminary analysis to answer relevant research questions using course materials
• Home Assignments
  Intermediate semester work on solving one of the problems related to the social sciences with the help of programming. Based on the materials of past seminars.

Interim Assessment

• 2026/2027 2nd module
  0.6 * Final project + 0.4 * Home Assignments

Bibliography

Recommended Core Bibliography

• Md. Jalal Uddin, M.J., Nishat Rayhana Eshita, N.R., Md. Asif Newaz, M.A., Naiem Sheikh, N., Afifa Talukder, A., Aysha Akter, A., Md. Habibur Rahman, M.H., & Md. Babul Miah, M.B. (2022). Scientific Data Analysis and Visualization with Python. https://doi.org/10.5281/ZENODO.7592894

Recommended Additional Bibliography

• Cansdale, A. (2021). How exploring Python can level up your data visualization. The Biochemist, 43(5), 4-7. https://doi.org/10.1042/bio_2021_169
• Joshi, A., & Tiwari, H. (2023). An Overview of Python Libraries for Data Science. Journal of Engineering Technology and Applied Physics, 5(2), 85-90. https://doi.org/10.33093/jetap.2023.5.2.10

Authors

• BARYKIN IAROSLAV ANDREEVICH