Бакалавриат
2026/2027
Информационные компьютерные системы и программирование на Python
Статус:
Курс по выбору (Международная программа по экономике и финансам)
Кто читает:
Международный институт экономики и финансов
Где читается:
Международный институт экономики и финансов
Когда читается:
1-й курс, 1, 2 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
4
Контактные часы:
80
Course Syllabus
Abstract
The course introduces Python as a powerful general-purpose tool for data manipulation, analysis, refactoring and many more. This course outlines the basics of Python and it’s libraries that are most important for financial data handling: pandas and numpy, exploring their powerful abilities in computation.
Learning Objectives
- The main aim of the course is to accommodate students with the full range of fundamentals of python, including concepts like functions, OOP, error-handling and etc. It also partially focuses on exploring such important concepts as git and docker, which come extremely handy in the cases when someone else’s work needs verification and/or reproduction.
Expected Learning Outcomes
- Apply Functions Syntax. Use Computational and financial Excel functions
- Use Computational and financial Excel functions.
- ● Apply basic Excel function knowledge: in particular, knows how to convert data from one type to another, works with combined formulas and functions (simple ones like SUM, dollar sign, useful functions like SUMMESLY and VPR), including formula stuffing, stretching formulas, tables, copying data from one sheet to another, switching cell reference styles, fixing cells in formulas
- • Knows the rules of Independent Assessment of Digital Literacy • Knows the basics of Media Literacy and Online Ethics. • Uses rules and recommendations of Media Literacy for communicating in the web with other users. • Tracks and clears own digital footprints on the web. • Recognizes fake news on the web domain.
- Understanding the basic way of pythonic workflow, data and code organization
- Understanding how to apply basic mathematical methods (primarily from calculus) in python (numpy) and how to do primitive data manipulations in it (pandas)
- Confident use of various digital devices and office programs
- Ability to analyze and critically evaluate information from various digital sources
- Knowledge of personal data protection methods
Course Contents
- Digital literacy
- Using built-in functions for data analysis
- Python basics
- Graphical Data Analysis in MS Excel
- Using Formulas and formatting for Conditional Analysis
- MS Excel Add-ins for solving economic tasks
- Working with large series of data
- Python extensions for tabular and multidimensional data
- Python OOP
- Python extensions for unit testing
- Intro to Docker
- Python for statistical and descriptive analysis
- Revision
Assessment Elements
- Digital literacy home assignments (tests)
- Home assignments
- Control work: In-class assignment
- Exam: In-class assignmentIn order to get a passing grade for the course, the minimum score should not be less than 20/100
Interim Assessment
- 2026/2027 2nd module0.15 * Home assignments + 0.5 * Exam: In-class assignment + 0.1 * Digital literacy home assignments (tests) + 0.25 * Control work: In-class assignment
Bibliography
Recommended Core Bibliography
- Learning Python : [covers Python 2.5], Lutz, M., 2008
- Жуков Р.А. - Язык программирования Python. Практикум - 978-5-16-015638-5 - ИНФРА-М - 2024 - https://znanium.ru/catalog/product/2131861 - 2131861 - ZNANIUM
- Изучаем Python. Т.1: ., Лутц, М., 2020
- Изучаем Python. Т.2: ., Лутц, М., 2020
Recommended Additional Bibliography
- Python и анализ данных : первичная обработка данных с применением pandas, NumPy и Jupiter, Маккинни, У., 2023
- Объектно-ориентированное программирование с помощью Python, Кальб, И., 2024