Master
2025/2026
Mentor's Seminar
Type:
Compulsory course (Data Analytics and Social Statistics)
Delivered by:
International Laboratory for Applied Network Research
When:
2 year, 1-3 module
Open to:
students of one campus
Instructors:
Nataliya Matveeva
Language:
English
Course 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
- The planning by undergraduates of their own educational and scientific trajectories and their implementation, as well as correction, if necessary.
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
- 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
- Term paper proposal
- Term paper presentation
- Mater thesis proposal
- Master thesis presentation
Interim Assessment
- 2024/2025 4th module0.6 * Term paper presentation + 0.6 * Term paper presentation + 0.4 * Term paper proposal + 0.4 * Term paper proposal
- 2025/2026 3rd module0.6 * Master thesis presentation + 0.6 * Master thesis presentation + 0.4 * Mater thesis proposal + 0.4 * Mater thesis proposal
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