Master 2023/2024

Mentor's Seminar

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

Area of studies: Economics

Delivered by: Department of Management

Where: St.Petersburg School of Economics and Management

When: 1 year, 1-4 module

Mode of studies: offline

Open to: students of one campus

Instructors: Pavel Sergeevich Molchanov, Anastasiia Pleshkova, Natalia Volkova

Master’s programme: Data Analytics for Business and Economics

Language: English

ECTS credits: 1

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
• Term paper discussion

Assessment Elements

• Class participation
  Participation in class discussion and completion the questionnaire
• Group presentation
  the topic is "Soft and data skills in data analytics"
• Class participation
  Individual or group discussion after the term papaer's pre-defence.

Interim Assessment

• 2023/2024 4th module
  0.4 * 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

Authors

• VOLKOVA Natalia VLADIMIROVNA