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Postgraduate seminar

2024/2025
Учебный год
ENG
Обучение ведется на английском языке
3
Кредиты

Преподаватель

Course Syllabus

Abstract

The program of the academic discipline “Postgraduate Seminar” is designed to prepare future researchers in the field of computer science. This course provides students with the opportunity to obtain in-depth knowledge and skills necessary for conducting independent research and writing a dissertation. The course will cover the theoretical foundations of computer science, modern methods of data analysis, and practical aspects of software development and system design
Learning Objectives

Learning Objectives

  • The goal of the Graduate Seminar course is to prepare students for independent research work in computer science, including theoretical and practical research, software development and system design.
Expected Learning Outcomes

Expected Learning Outcomes

  • Develop critical thinking and the ability to analyze scientifically.
  • Explore new directions and methodologies within computer science
  • Have a thorough knowledge of algorithms, data structures, information theory and other fundamental disciplines
  • Analyze and apply theoretical knowledge to solve practical problems.
  • Master key concepts and methods used in modern computer science research.
  • Consider security, reliability and scalability issues in system design
  • Integrate system components.
  • Develop software architecture
  • Design complex information systems.
  • Effectively communicate their research findings to colleagues and a wide audience.
  • Participate in professional conferences.
  • Critically analyze the literature.
  • Prepare reports, articles and presentations.
  • Behave responsibly and transparently in the research processPrepare reports, papers, and presentations.
  • Comply with ethical standards and legal requirements when conducting research.
  • Ensure confidentiality and protection of personal data.
  • Comply with key laws and regulatory requirements relating to research.
  • Prepare and defend a PhD thesis.
  • Be proficient in research writing techniques.
  • Know the requirements for the design and content of the dissertation.
  • To possess the skills of public speaking and defense of his/her work before the commission.
Course Contents

Course Contents

  • Theoretical foundations of computer science
  • Methods of data analysis
  • Scientific communication
  • Ethics and legal aspects of scientific research
  • Preparation of dissertation
Assessment Elements

Assessment Elements

  • non-blocking Preparation of reports at seminars and scientific conferences
  • non-blocking Work on scientific articles: writing and publishing articles in peer-reviewed journals
  • non-blocking Reporting on project work: regular progress reports on the dissertation project
  • non-blocking Presentation at a scientific seminar or scientific conference
  • non-blocking Dissertation defense
Interim Assessment

Interim Assessment

  • 2022/2023 2nd semester
    0.2 * Preparation of reports at seminars and scientific conferences + 0.2 * Preparation of reports at seminars and scientific conferences + 0.4 * Presentation at a scientific seminar or scientific conference + 0.4 * Presentation at a scientific seminar or scientific conference + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals
  • 2023/2024 2nd semester
    0.2 * Preparation of reports at seminars and scientific conferences + 0.2 * Preparation of reports at seminars and scientific conferences + 0.4 * Presentation at a scientific seminar or scientific conference + 0.4 * Presentation at a scientific seminar or scientific conference + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals
  • 2024/2025 2nd semester
    0.4 * Dissertation defense + 0.4 * Dissertation defense + 0.2 * Preparation of reports at seminars and scientific conferences + 0.2 * Preparation of reports at seminars and scientific conferences + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Reporting on project work: regular progress reports on the dissertation project + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals + 0.2 * Work on scientific articles: writing and publishing articles in peer-reviewed journals
Bibliography

Bibliography

Recommended Core Bibliography

  • Applied multivariate statistical analysis, Johnson, R., 2014
  • Introduction to the theory of computation, Sipser, M., 2016
  • Young, J., McGrath, R., & Filiault, S. (2009). Review: Linda Dale Bloomberg & Marie F. Volpe (2008). Completing Your Qualitative Dissertation: A Roadmap From Beginning to End ; Reseña: Linda Dale Bloomberg & Marie F. Volpe (2008). Completing Your Qualitative Dissertation: A Roadmap From Beginning to End. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A60E3D7E

Recommended Additional Bibliography

  • Hastie, T., Tibshirani, R., & Friedman, J. H. (2009). The Elements of Statistical Learning : Data Mining, Inference, and Prediction (Vol. Second edition, corrected 7th printing). New York: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=277008
  • Introduction to the theory of computation, Sipser, M., 2013
  • Trevor Hastie, Robert Tibshirani, & Jerome Friedman. New York. (n.d.). Book Reviews 567 The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.45E1D521
  • Young, J., McGrath, R., & Filiault, S. (2009). Completing Your Qualitative Dissertation: A Roadmap From Beginning to End. Forum: Qualitative Social Research, 10(3), 1–10.

Authors

  • Kaliagin Valerii Aleksandrovich

 

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