Введение в программирование на Python

Магистратура 2025/2026

Статус: Курс по выбору (Обучение и оценивание как наука)

Кто читает: Департамент образовательных программ

Где читается: Институт образования

Когда читается: 2-й курс, 1 модуль

Охват аудитории: для всех кампусов НИУ ВШЭ

Преподаватели: Павлова Анна Андреевна

Язык: английский

Кредиты: 3

Контактные часы: 6

Full Syllabus Ask Question

Abstract

The course is aimed at learning the basics of Python for quantitative data analysis in psychological research. During the course, students will get acquainted with the functionality of the main Python libraries for data analysis: Pandas, Numpy, Matplotlib, Seaborn, and also learn the basics of machine learning using the Scikit-learn library. The course involves taking an online Intro to Programming in Python course

Learning Objectives

Mastering the Python programming language for solving a number of tasks in the field of data analysis

Expected Learning Outcomes

Uses basic Python syntax to work with quantitative data
Preprocesses data using numpy and pandas libraries (deleting/filling in gaps, creating new variables, managing variable types)
Tests hypotheses about the relationship between variables using Python programming language packages and libraries (for example, Scipy, statsmodels)
Visualizes quantitative data using the seaborn and matplotlib libraries of the Python programming language
Selects suitable data analysis methods (for example, machine learning methods) for a specific task and implements them using the Python programming language

Course Contents

The basics of Python
Pandas
Numpy
Basic statistical analysis
Data visualization
Intro to ML
Final project

Assessment Elements

Course Intro to Programming in Python – Stepik sertificate
Final project

Interim Assessment

2025/2026 1st module
0.4 * Course Intro to Programming in Python – Stepik sertificate + 0.6 * Final project

Bibliography

Recommended Core Bibliography

Guido Van Rossum, & Fred L. Drake. (2004). Python/C API Reference Manual Release 2.3.4. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.2FEE239A

Recommended Additional Bibliography

Python for data analysis : data wrangling with pandas, numPy, and IPhython, Mckinney, W., 2017

Authors

SHALOM KSENIYA VLADIMIROVNA

Course Syllabus