Python for Data Science and AI

2021/2022

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Business Informatics

Course type:

Bridging course

When:

1 year, 1 module

Instructor

Kuznetsova, Yulia A.

Course Syllabus

Abstract

Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries. During this MOOC bridging course (https://www.coursera.org/learn/python-for-applied-data-science-ai) you will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and solving real-world problems in Python.

Learning Objectives

• Become familiar with key Python functions, objects, and classes
• Learn about Python fundamentals, Python data structures, and working with data in Python

Expected Learning Outcomes

• Student builds programs in Python.
• Student can read and write files in Python.
• Student uses concepts of conditions and branching in Python programming.
• Students uses key Python functions, objects, classes, and data structures for working with data in Python.

Course Contents

• Python Basics
• Python Data Structures
• Python Programming Fundamentals
• Working with Data in Python

Assessment Elements

• Coursera Course Certificate or Written test
  Students who do not have a certificate of Coursera course will have to pass the written exam (test).
• Final written test
  The final score is rounded by dropping the fractional part.

Interim Assessment

• 2021/2022 1st module
  0.5 * Coursera Course Certificate or Written test + 0.5 * Final written test

Bibliography

Recommended Core Bibliography

• Eric Matthes. (2019). Python Crash Course, 2nd Edition : A Hands-On, Project-Based Introduction to Programming: Vol. 2nd edition. No Starch Press.

Recommended Additional Bibliography

• Dr. Ossama Embarak. (2018). Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems. Apress.
• Плас Дж. Вандер. Python для сложных задач: наука о данных и машинное обучение. - Санкт-Петербург : Питер, 2018. - 576 с. - ISBN 978-5-496-03068-7. - URL: https://ibooks.ru/bookshelf/356721/reading (дата обращения: 12.10.2020). - Текст: электронный.