Programming in Python

2026/2027

Учебный год

ENG

Обучение ведется на английском языке

4

Кредиты

Кто читает:

Департамент социологии

Статус:

Курс по выбору

Когда читается:

2-й курс, 1, 2 модуль

Преподаватель

Барыкин Ярослав Андреевич

Course Syllabus

Abstract

This course aims to build competencies in understanding and writing programming code in Python. It will cover the topics students need to successfully master the basic data types and syntax of Python.

Learning Objectives

• To learn Python programming basics enough for understanding the code written by other people and run elementary Python programs.

Expected Learning Outcomes

• Create variables, write the information into variables, call the variables
• Correctly recognize Python data types and convert one into another if necessary.
• Understand the program errors and fixing them
• Use boolean data type, comparison operators, logical operators
• Correctly write conditionals
• Use loops to optimize repetitive actions, break the loop on condition
• Distinguish between mutable and immutable data types
• Run the operations on sets, meaningfully interpret the results.
• Create a dictionary and add and call the information from it
• Sort sequences, sort the dictionary values by keys.
• Write customized functions
• Open text files, create and write the information in the text files
• Read the files, process and analyze the data
• Working with string data type, string indexing and formatting.
• Import and use the developed external functions

Course Contents

• Introduction to Python. Installation, Interpreter, and IDE.
• Data types. Data input and output. Output formatting. Arithmetic. Errors.
• Conditionals. Boolean Logic. If-Statements. Sequences (lists, tuples, strings).
• Loops. For-loops. While-loops. Nested data structures.
• Collections (sets, dicts).
• Functions and libraries. Writing functions. Global and local variables. Importing functions from libraries.
• Working with files.
• Solving tasks with Python. Intro to projects.
• Tasks and projects: advanced tasks and group projects.

Assessment Elements

• Midterm test
• Final exam
• Short quizzes
  Short 10-min test to evaluate the progress on online course.
• Home assignment
  The results of individual home assignment work. The assignment is completed individually and submitted through SmartLMS or another approved platform. The assignment checks the ability of students to write code in Python and solve programming tasks based on the course material.
• Independent in-class work
  The results of student's work in class (under supervision of a lecturer).

Interim Assessment

• 2026/2027 2nd module
  0.1 * Short quizzes + 0.25 * Final exam + 0.2 * Independent in-class work + 0.2 * Home assignment + 0.25 * Midterm test

Bibliography

Recommended Core Bibliography

• Bill Lubanovic. (2019). Introducing Python : Modern Computing in Simple Packages. [N.p.]: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2291494

Recommended Additional Bibliography

• 9781491912140 - Vanderplas, Jacob T. - Python Data Science Handbook : Essential Tools for Working with Data - 2016 - O'Reilly Media - https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1425081 - nlebk - 1425081
• Eric Matthes. (2019). Python Crash Course, 2nd Edition : A Hands-On, Project-Based Introduction to Programming: Vol. 2nd edition. No Starch Press.
• Lutz, M. (2008). Learning Python (Vol. 3rd ed). Beijing: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=415392

Authors

• BARYKIN IAROSLAV ANDREEVICH