Bachelor
2024/2025
Data Structures
Type:
Elective course (Psychology)
Area of studies:
Psychology
Delivered by:
School of Psychology
Where:
Faculty of Social Sciences
When:
4 year, 1 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Nikita Kolachev
Language:
English
ECTS credits:
3
Contact hours:
6
Course Syllabus
Abstract
This interactive textbook was written with the intention of teaching Computer Science students about various data structures as well as the applications in which each data structure would be appropriate to use.
This textbook utilizes the Active Learning approach to instruction, meaning it has various activities embedded throughout to help stimulate your learning and improve your understanding of the materials we will cover. You will encounter STOP and Think questions that will help you reflect on the material, Exercise Breaks that will test your knowledge and understanding of the concepts discussed, and Code Challenges that will allow you to actually implement some of the algorithms we will cover.
Currently, all code challenges are in C++ or Python, but the vast majority of the textbook's content is language-agnostic theory of complexity and algorithm analysis. In other words, even without C++ or Python knowledge, the key takeaways of the textbook can still be obtained.
Bibliography
Recommended Core 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
Recommended Additional Bibliography
- Okasaki, C. (1998). Purely Functional Data Structures. Cambridge, U.K.: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=502386