Postgraduate course
2023/2024
Reading the Best Doctoral Dissertations in Computer Science
Type:
Elective course
Area of studies:
Postgraduate Studies
Delivered by:
School of Data Analysis and Artificial Intelligence
When:
1 year, 1 semester
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Sergei Kuznetsov
Language:
English
ECTS credits:
4
Contact hours:
38
Course Syllabus
Abstract
The course introduces the students to the best recently defended theses in computer science.
Learning Objectives
- The student should be able to make a presentation on a theses and analyze advantages and flaws of dissertations in the domain
Expected Learning Outcomes
- The students become aware of the general level of an excellent dissertation in data science: strength of results, reference to previous work, and presentation style.
Course Contents
- Best dissertations in theoretical computer science
- Best dissertations in Data Science
- Best dissertations in software engineering
Bibliography
Recommended Core Bibliography
- Theory of sample surveys, Gupta, A. K., 2011
Recommended Additional Bibliography
- Granados, N., & Gupta, A. (2013). Transparency Strategy: Competing with Information in a Digital World. MIS Quarterly, 37(2), 637–641. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=87371436
- Levendis, J. D. (2018). Time Series Econometrics : Learning Through Replication. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2016053