Algorithms and Data Structures

Bachelor 2023/2024

Type: Compulsory course

Area of studies: Business Informatics

Delivered by: Department of Business Informatics

Where: Graduate School of Business

When: 2 year, 1, 2 module

Mode of studies: offline

Open to: students of one campus

Language: English

ECTS credits: 3

Contact hours: 36

Full Syllabus

Abstract

The course is dedicated to the basics of design and analysis of algorithms. It also involves learning advanced algorithms, data structures and basics of the automata theory. The lectures and practical classes are closely inter-related. The lectures are primarily intended to introduce new topics, whereas the practical classes are intended for solving specific problems by coding programs in C++ or Python. Successful completion of “Introduction to Programming” course is the sole prerequisite for being enrolled in this course.

Learning Objectives

The course is aimed to provide students with necessary knowledge and tools to write programs in python and understand code written by others.

Expected Learning Outcomes

Be able to find and read documentation on python libraries not covered by the course.
Be able to set up python environment
Understand key concepts of programming and apply them
Be able to write scripts in python

Course Contents

1. Introduction to programming and the Python language
2. Python script mode. Conditional execution
3. Loops
4. Bitwise operations. Error handling techniques
5. Functions and modules. Name scopes. Recursive algorithms
6. Python data model. Lists, sets, tuples.
7. Introduction to algorithmic complexity. Sorting algorithms.
8. Strings. Advances techniques of text processing, regular expressions
9. File input-output

Assessment Elements

Homework assignments
Home assignments for the relevant topics discussed in the class in a form of small problems in the web IDE.
Final exam
The set of small programming auto-tested tasks.

Interim Assessment

2023/2024 2nd module
0.3 * Final exam + 0.7 * Homework assignments

Bibliography

Recommended Core Bibliography

Downey, A. (2015). Think Python : How to Think Like a Computer Scientist (Vol. Second edition). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1105725
Eric Matthes. (2019). Python Crash Course, 2nd Edition : A Hands-On, Project-Based Introduction to Programming: Vol. 2nd edition. No Starch Press.
Learning Python : [covers Python 2.5], Lutz, M., 2008
Lutz, M. (2011). Programming Python : Powerful Object-Oriented Programming (Vol. 4th ed). Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=415412
Sweigart, Al. Automate the boring stuff with Python: practical programming for total beginners. – No Starch Press, 2015. – 505 pp.
Программируем на Python, Доусон, М., 2015

Recommended Additional Bibliography

Baka, B. (2017). Python Data Structures and Algorithms. Birmingham, U.K.: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1528144

Course Syllabus