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Course Syllabus

Master 2023/2024

Mentor's Seminar

Type: Compulsory course
Area of studies: Applied Mathematics and Informatics
Delivered by: International laboratory for Applied Network Research
Where: Faculty of Social Sciences
When: 1 year, 1-4 module
Mode of studies: offline
Open to: students of one campus
Instructors: Ivan Alexandrovich Klimov
Master’s programme: Applied Statistics with Network Analysis
Language: English
ECTS credits: 1
Contact hours: 8

Course Syllabus

Full Syllabus

Abstract

The seminar is aimed at facilitating the planning by undergraduates of their own educational and scientific trajectories and their implementation, as well as correction, if necessary. This goal is achieved through individual meetings of undergraduates with an academic mentor, meetings within small teams and within the entire academic group. The agenda of meetings is formed in advance by both the mentor and undergraduates, after which the mentor chooses the format for the implementation of the agenda.
Learning Objectives

Learning Objectives

  • the planning by undergraduates of their own educational and scientific trajectories and their implementation, as well as correction, if necessary.
Expected Learning Outcomes

Expected Learning Outcomes

  • Understanding the possibilities of the educational program, choosing a priority training track
  • Understanding your interest and choosing the project topic, problematization of the topic
  • Mastering the skills of research and academic work
  • The ability to build a research project in the context of an educational program
  • Planning the development of analytical skills
  • Reflection on possible problems and difficulties
Course Contents

Course Contents

  • The structure of the educational program and the choice of the
  • Choosing a project topic.
  • Mastering the skills of research and academic work.
  • Preparation of Master Thesis
Assessment Elements

Assessment Elements

  • blocking Provision of a training plan for the educational program for the selected track
  • blocking Provision of a Term Paper plan
  • blocking Providing a Master Thesis research and training plan
  • blocking Providing a Master Thesis plan
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.5 * Provision of a Term Paper plan + 0.5 * Provision of a training plan for the educational program for the selected track
  • 2024/2025 3rd module
    0.5 * Providing a Master Thesis plan + 0.5 * Providing a Master Thesis research and training plan
Bibliography

Bibliography

Recommended Core Bibliography

  • Attewell, P. A., & Monaghan, D. B. (2015). Data Mining for the Social Sciences : An Introduction (Vol. First edition). Oakland, California: University of California Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=967323

Recommended Additional Bibliography

  • Chu, W. W. (2013). Data Mining and Knowledge Discovery for Big Data : Methodologies, Challenge and Opportunities. Heidelberg: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=643546
  • Larose, D. T., & Larose, C. D. (2015). Data Mining and Predictive Analytics. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=958471