What will you learn?
The Programme brings together traditional courses in general and strategic management, business strategy and international business along with the application of data analytics for these areas. Master in Management & Analytics for Business places an emphasis on data-driven decision-making, on data-based business models, and on digital transformation of business. This expertise is expected to be the most relevant and demanded by employers.
The programme provides rigorous theoretical foundations during the first year of study – common for all students; and domain-oriented business analytical training in the second year. We invite students to have deep cutting-edge training in People Analytics (HR) or Customer Analytics (Marketing).
The programme targets bachelors with IT, math, economics and management background. Eligible students must have good command of English as demonstrated by international certificates or exam (except native English speakers and students who have completed a degree exclusively in English).
Research and Projects
The programme has a track on Research. We provide students with analytical skills by taking part in advanced training for business research methods and projects of HSE research centres. That facilitates their further education on leading international PhD programmes in Economics and Management. The most motivated and talented students will be granted an opportunity to integrate their research into projects of the International Laboratory of Intangible-driven Economy.
Research Seminars are conducted by leading experts in Business studies and are running for the whole period of study. Students write academic or project-based research master thesis under supervision of world class professionals: Felix Lopez-Itturiaga (University of Valladolid), Carlos Fernandez-Jardon (University of Vigo), Dennis Coates (UMBC), Romie Littrell (HSE University), Angel Barajas (HSE University).
The programme offers three months’ business internships for all students. Moreover, we encourage the best students to have longer period of training on the base of HSE business partners: Danone, Nissan, 2GIS, JTI, BAT, Philip Morris, Bosch-Siemens, KPMG, Ernst & Young, Deloitte, McKinsey, VTB, Sberbank among others. That enriches the programme curriculum but more importantly enables substantially better personal placement and future employability.
Exchange programs provide students with the chance to spend one semester at a partner university abroad.
- General management ( 3 credits)
- Business research methods (3 credits)
- Statistical approach to Data Analysis (3 credits)
- International Business and Global Stratagies (3 credits)
- Practical Machine Learning Methods for Data Mining (3 credits)
- Business Strategies for Emerging Markets (3 credits)
- Financial Management and Investment (3 credits)
- Knowledge and Information management (3 credits)
- Two University Pool Courses (MAGO-LEGO) (3 credits)
I. People Analytics
- People Analytics: Prediction of Performance & Prescription of Policy (3 credits)
- Staffing Analytics Overview (3 credits)
- Performance Evaluation: Data and Tools (3 credits)
- Talent Analytics: Data and Tools (3 credits)
II. Customer Analytics
- Consumer Behaviour (3 credits)
- Database Marketing and Analytical CRM (3 credits)
- Advanced Marketing Models (3 credits)
- Text and Social Media Analytics (3 credits)
III. Research distinction
- Advanced Research Methods for Business (3 credits)
- Empirical Methods and Applications in Business (3 credits)
- Microeconometrics and Empirical Corporate Finance: Predictive and Prescriptive Analysis (3 credits)
- Dynamic Optimisation for Business Research (3 credits)
IV. Sports Analytics
- Sports Economics and Finance (3 credits)
- Fans, Media and Technology: The Commercial Side of Sports (3 credits)
- Managing sports events: facilities, operations and economic impact (3 credits)
- Sports Performance (3 credits)
V. Applied Statistics with Network Analysis
You have to choose three courses among following ones:
- Introduction to Network Analysis (4 credits)
- Data Mining (4 credits)
- Exploratory Data Analysis (4 credits)
- Applied Linear Models I (4 credits)
- Contemporary Data Analysis: Methodology and Methods of Interdisciplinary Research (4 credits)
- Analysis of Covariance Models (4 credits)
- Methods of Statistical Consulting (4 credits)