Master
2024/2025
Mentor's Seminar
Type:
Compulsory course (Data Analytics for Business and Economics)
Area of studies:
Economics
Delivered by:
Department of Management
When:
1 year, 1-4 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Sergey G. Kokovin,
Pavel Sergeevich Molchanov,
Anastasiia Pleshkova,
Natalia Volkova,
Рослова Александра Олеговна
Master’s programme:
Data Analytics for Business and Economics
Language:
English
ECTS credits:
1
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
- Term paper discussion
Assessment Elements
- Group presentationthe topic is "Soft and data skills in data analytics"
- Class participationIndividual or group discussion after the term papaer's pre-defence.
- Class participationParticipation in class discussion and completion the questionnaire
Interim Assessment
- 2024/2025 4th module0.4 * Class participation + 0.3 * Class participation + 0.3 * 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