• A
  • A
  • A
  • АБB
  • АБB
  • АБB
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта
Аспирантура 2023/2024

Лучшие диссертации по компьютерным наукам

Статус: Курс по выбору
Направление: 00.00.00. Аспирантура
Когда читается: 1-й курс, 1 семестр
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 4
Контактные часы: 38

Course Syllabus

Abstract

The course introduces the students to the best recently defended theses in computer science.
Learning Objectives

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

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

Course Contents

  • Best dissertations in theoretical computer science
  • Best dissertations in Data Science
  • Best dissertations in software engineering
Assessment Elements

Assessment Elements

  • non-blocking Активность на занятиях
  • non-blocking Презентаця диссертации
Interim Assessment

Interim Assessment

  • 2023/2024 1st semester
    0.2 * Активность на занятиях + 0.8 * Презентаця диссертации
Bibliography

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

Authors

  • Антропова Лариса Ивановна
  • KUZNETSOV SERGEY OLEGOVICH