Master of Science in Business Analytics

About the program

Businesses need to start managing data as a strategic asset. Data analytics and machine learning not only offer quantitative insight, but also improve evidence-based decision-making. Business Analytics is where data science meets business strategy, a must for future-proofing businesses. The curriculum provides a unique mix of analytics, computer science and business, essential for better business decisions.

Download our Data Sheet

Watch our MS in Business Analytics Intro Video

At a glance:

Become a business decision-maker who is able to understand data and how an actionable analytics strategy can drive business value.

  • Weekday classes, twice a week for full time, once a week for part time from 1:30 p.m to 8pm. Some electives are held other days on weekends.
  • Features a capstone project with an industry partner
  • Full-time path (12 months)
  • Part-time path (24 months) – same program, same classes, but spread over two years
  • Tuition: EUR 15,000
  • 36 Credits (core courses: 19, electives: 9, capstone project: 8)

You will learn how to:

  • Use statistical analysis to find patterns and evaluate past and future business interventions
  • Write code, and apply predictive analysis and models of causal analysis
  • Collect and parse data, and translate it into actionable insights
  • Get familiar with key tools, frameworks and platforms, and learn to implement processes in production
  • Manage a data-driven business and create knowledge from big data and other sources of quantitative information
  • Collaborate with software development specialists, quantitative analysts, and present your analysis in a clear and effective manner
  • Thrive in a truly multicultural environment

Where your degree can take you:

  • Data science departments of large corporations, where you will be responsible for analyzing and managing data
  • Management roles, supervising data scientists
  • Smaller companies in need of someone to set up or revamp data collection and analytics efforts

Admissions requirements

Admission is based on previous studies (including specific courses), professional experience, as well as the statement of purpose and letters of recommendation.

Click here for more information about the admissions process and the list of admissions requirements.

Application Deadlines

  • June 1, 2018 (for students who need a visa)
  • June 30, 2018 (for non-visa students)

We may accept late applications from non-visa students through August 15, 2018.

We can start processing your application once you have submitted your CEU Application Form, CV, and Motivation Letter. For any outstanding documents please upload a Microsoft Word document stating the expected date of receipt.

Head of program: Prof. Gábor Békés and Prof. Achilles Georgiu

Program Administrator: Eszter Fuchs (room: N13 414, Contact person by email)