Master 2025/2026

Mentor's Seminar

Type: Compulsory course (Data Analytics for Business and Economics)

Delivered by: Department of Management

When: 1 year, 1-4 module

Open to: students of one campus

Instructors: Anastasiia Pleshkova, Natalia Volkova

Language: English

Contact hours: 16

Course Syllabus

Abstract

The mentor's seminar is intended for joint activities of the academic mentor and the student to solve the following tasks: determining individual educational results that the student intends to achieve during the development of the program; selection and coordination of academic disciplines, relevant projects and seminars; individual consultation of the student with the mentor about the progress of the program and the degree of achievement of results; adjustment of the individual curriculum in the case of of necessity.

Learning Objectives

• The aim of this seminar is to support students in building their individual learning trajectories and defining individual educational outcomes.

Expected Learning Outcomes

• To take ethical approach to work in international and multicultural teams
• Students can choose and formulate appropriate directions of their research, evaluate their practical value and theoretical contribution
• Able to identify soft and data skills relevant to a particular business area
• Able to implement sustainable development principles in research projects

Course Contents

• Introduction to the Master's program and data analytics
• Sustainable development goals in management and economics
• Skills for analysts
• Master thesis discussion

Assessment Elements

• Group presentation
  The example of the topic is "Soft and data skills in data analytics".
• Class activity
  Participation in class discussion and completion the questionnaire
• Class activity
  Individual or group discussion regarding master thesis.

Interim Assessment

• 2025/2026 4th module
  0.25 * Class activity + 0.25 * Class activity + 0.5 * Group presentation

Bibliography

Recommended Core Bibliography

• UI AHSAAN, S., & MOURYA, A. K. (2019). Big Data Analytics: Challenges and Technologies. Annals of the Faculty of Engineering Hunedoara - International Journal of Engineering, 17(4), 75–79.

Recommended Additional Bibliography

• Pyne, S., Prakasa Rao, B. L. S., & Rao, S. B. (2016). Big Data Analytics : Methods and Applications. New Delhi, India: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1281845

Authors

• Volkova Natalia Vladimirovna