Bachelor 2023/2024

Introduction into Python

Type: Compulsory course (International Business)

Area of studies: Management

Delivered by: Big Data and Information Retrieval School

Where: Graduate School of Business

When: 2 year, 1 module

Mode of studies: distance learning

Online hours: 50

Open to: students of one campus

Instructors: Tatiana Perevyshina

Language: English

ECTS credits: 3

Contact hours: 24

Course Syllabus

Abstract

The Python programming language is one of the easiest to learn and popular programming languages. The aim of the course is to learn the basic constructs of the Python language, which will be useful in solving a wide range of problems - from data analysis to the development of new software products. The course provides the necessary foundation for mastering more specialized areas of the Python language, such as machine learning, statistical data processing, data visualization, and many others. The course offers a large number of programming tasks, arranged in order of increasing complexity, which allows you to consolidate the studied material in practice.

Learning Objectives

• Students achieve excellent results by doing a considerable amount of practical exercises both in class and at home and taking part in group projects

Expected Learning Outcomes

• Know and differentiate basic Python data types. Choose the correct data types based on the problem in hand
• Know and understand basic Python syntax
• Load and use additional Python modules
• Use Python for routine tasks automation
• Use Python to read and write structured and unstructured files
• Write their own functions
• Use Jupyter Notebook or similar program

Course Contents

• Intro and logistics. Anaconda and Jupyter Notebook. First program.
• Data types: integers and strings. Input and output. Strings formatting.
• Data types: floating-point numbers and boolean. Logical operators. Conditionals.
• While loop.
• Data types: lists and tuples. For loop.
• For Loop (2nd Part)
• Methods I (Strings)
• Methods II (Lists)
• Review I.
• MIDTERM
• Data types: sets and dictionaries.
• Nested Structures
• Functions
• Working with text files in Python.
• Review II
• TEST

Assessment Elements

• HW
• Oral survey
  формат сдачи контрольного мероприятия зависит от формата проведения занятий (для онлайн-занятий – возможно использование прокторинга)
• Quizes
  формат сдачи контрольного мероприятия зависит от формата проведения занятий (для онлайн-занятий – возможно использование прокторинга)
• MT
  формат сдачи контрольного мероприятия зависит от формата проведения занятий (для онлайн-занятий – возможно использование прокторинга)

Interim Assessment

• 2023/2024 1st module
  Final = min(8, ROUND(grade*0.9)) grade = HW *0.15 + Oral survey *0.25 + Quizes *0.3 + MT*0.3 Комментарий к формуле: Пункт ПОПАТКУСа 69. Независимый экзамен может иметь факультативные или обязательные дисциплины-пререквизиты, включенные в учебный план образовательной программы. Степень обязательности дисциплин-пререквизитов определяется в программе независимого экзамена или в иных локальных нормативных актах, описывающих особенности формирования компетенций. Оценка, выставляемая по итогам промежуточной аттестации по дисциплине-пререквизиту к независимому экзамену по цифровой компетенции, не может быть больше 8 баллов.

Bibliography

Recommended Core Bibliography

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

Recommended Additional Bibliography

• Taieb, D. (2018). Data Analysis with Python : A Modern Approach. Birmingham, UK: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1993344