Programming in R and Python

2024/2025

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Международная лаборатория прикладного сетевого анализа

Статус:

Курс обязательный

Когда читается:

1-й курс, 1 модуль

Преподаватели

Капустина Лика Владимировна

Семенова Анна Михайловна

Course Syllabus

Abstract

Students who have never programmed are afraid that it is difficult. This course is designed to introduce them to the basics of programming languages such as R and Python. This course will discuss the difference between these languages, the strengths of each of them. Students will learn the basics of programming and working with these languages.

Learning Objectives

• to provide students with the basic R and Python skills that will be required in other courses in the programme

Expected Learning Outcomes

• be able to create and work with vectors, matrices and lists
• be able to upload files to R space
• be able to visualize data
• have skills on performing descriptive statistics, exploratory data analysis
• know how to build simple and basic models

Course Contents

• Data formats
• Starting working with data
• Exploratory data analysis
• Visualization
• Basic linear regression
• R Basics

Assessment Elements

• Quizzes
• Homework assignments
• Final project

Interim Assessment

• 2024/2025 1st module
  0.5 * Final project + 0.2 * Homework assignments + 0.3 * Quizzes

Bibliography

Recommended Core Bibliography

• W. N. Venables, & D. M. Smith. (2012). D.M.: An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics Version 2.15.0. R-project.org.

Recommended Additional Bibliography

• Simon N. Wood. (2017). Generalized Additive Models : An Introduction with R, Second Edition: Vol. Second edition. Chapman and Hall/CRC.

Authors

• Pavlova Irina Anatolevna
• SEMENOVA ANNA MIKHAILOVNA
• Капустина Лика Владимировна