Master 2026/2027

Introduction to Python

Type: Compulsory course (Economics and Economic Policy)

Delivered by: Department of Applied Economics

Where: Faculty of Economic Sciences

When: 1 year, 1 module

Online hours: 40

Open to: students of all HSE University campuses

Instructors: Konstantin Polyakov

Language: English

ECTS credits: 3

Contact hours: 14

Course Syllabus

Abstract

This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course. This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis.

Learning Objectives

• This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python.

Expected Learning Outcomes

• Installing and using Python
• Strings Processing in Python
• Variables and expressions
• Use Loop and Conditional Statements
• Definition of functions in Python
• Files Processing in Python
• The Concept of "dictionary" in Python
• The Concept of "list" in Python
• The Concept of "tuple" in Python
• Regular expressions in Python
• Classes and Objects in Python

Course Contents

• Intro-01. Python basics. Variables, expressions and statements.
• Intro-02. Python control structures.
• Intro-03. Functions.
• Intro-04. Files
• Intro-05. Data structures.
• Intro-06. Regular Expressions
• Intro-07. Object-Oriented Programming

Assessment Elements

• Final test - 2
  A mix of multiple choice questions and open-ended questions.
• The entrance test
  A multiple choice question test. One answer is correct.
• Final test - 1
  A mix of multiple choice questions and open-ended questions.
• Creative assignment
  Preparation of a two‑minute video clip on the topic “Python in data science”. The use of AI is prohibited. It is recommended to use screen recording tools. Copying video materials from other clips is allowed, but not more than 25 percent. The author is always present on screen and provides comments in Russian. The use of one’s own code in examples is encouraged.

Interim Assessment

• 2026/2027 1st module
  Each student chooses one of two options: the course grade is determined based on the results of the entrance test (the score obtained for the test is indicated) or based on the results of two final tests and a creative assignment. The grade is based on the minimum score obtained for these assessment elements (the entrance test is not taken into account).

Bibliography

Recommended Core Bibliography

• Severance, C. (2016). Python for Everybody : Exploring Data Using Python 3. Place of publication not identified: Severance, Charles. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsotl&AN=edsotl.OTLid0000336

Recommended Additional Bibliography

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

Authors

• Poliakov Konstantin Lvovich