Основы работы с данными

2026/2027

ID 1099695

Статус: Маго-лего

Кто читает: Департамент политологии и международных отношений

Где читается: Санкт-Петербургская школа социальных наук

Охват аудитории: для своего кампуса

Преподаватели: Аркатов Дмитрий Александрович

Язык: русский

Кредиты: 3

Контактные часы: 18

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Аннотация

This course introduces students to the fundamental tools and techniques used in data analysis, providing a solid foundation for understanding and interpreting data. Through hands-on activities and practical exercises, participants will learn how to collect, clean, analyze, and visualize data using popular software tools such as Excel, R, and Python.

Цель освоения дисциплины

Develop proficiency in R programming and RStudio, including data manipulation, cleaning, visualization, and application of basic statistical methods to real-world datasets
Build the ability to write modular, reusable, and well-structured R code, enabling efficient analysis and clear presentation of data insights.

Планируемые результаты обучения

Demonstrate proficiency in R programming, including working with vectors, lists, matrices, data frames, and factors to manipulate and manage data efficiently.
Import, clean, and preprocess real-world datasets using R, applying filtering, transformation, and merging techniques to prepare data for analysis.
Create informative and visually appealing static and interactive plots using base R, ggplot2, and plotly to communicate data insights effectively.
Develops modular, reusable, and well-structured R code, and applies best practices for project organization and reproducible workflows using RStudio and RMarkdown.

Содержание учебной дисциплины

Introduction to R and RStudio
Basic Data Structures
Data Frames and Data Import
Data Cleaning and Preprocessing
Functions and Code Modularity
Data Visualization
Working with Packages and Reproducible Workflows
Conditional Statements and Loops

Элементы контроля

Homework Assignments
Complete practical exercises and projects outside of class. Homework is designed to reinforce programming skills, data manipulation, visualization, and application of concepts covered in classes.
Final Test
A comprehensive assessment evaluating understanding of R programming, data handling, visualization, functions, and workflow organization. Includes theoretical questions and practical coding tasks.
Class Participation
Actively engage in discussions and in-class exercises. Participation reflects attentiveness, contribution to group activities, and willingness to ask and answer questions.

Промежуточная аттестация

2026/2027 4th module
0.3 * Class Participation + 0.3 * Homework Assignments + 0.4 * Final Test

Список литературы

Авторы

Аркатов Дмитрий Александрович

Программа дисциплины