Earn a valuable degree

The MS in Business Analytics program covers a unique mix of data analytics, computer science and business topics including programming, statistics with machine learning, big data and cloud computing, and data engineering. The program ranked #1 in Central Europe and #51+ in the world in the QS Business Masters Rankings 2020.

Learn to analyze and act upon insights from data. Understand how data analytics can drive business value. Complete your training with use case seminars, specialist courses on text mining, deep learning or agile project management and a capstone consulting project.

Study in Vienna

Apply now and study in Vienna, consistently ranked among the world’s most livable cities by the Economist Intelligence Unit. Located in the heart of Europe, the Austrian capital has much to offer, from a wide range of academic opportunities to vibrant student life.

Study and work at the same time

The MS in Business Analytics is designed expressly so you can study and work at the same time. Core courses and main elective courses run two days a week from 1:30 p.m. Some courses involve weekend-only classes.

Join full-time as a graduate or career changer. As a full-time student, you may land an internship at any time. Should this happen, you may request to change your status and become a part-time student.

Join part-time as a working professional. As a part-time student, you may request to extend your studies with a second year to continue taking elective courses or to complete your capstone project.

Boost your career

In 2020, 91% of our full-time students landed a job within three months of graduation.

Vienna is among Europe’s most buzzing financial services and technology hubs. Employers competing for international talent include DB Schenker, Deloitte, EATON, Franklin Templeton, Google, JP Morgan, LVMH, Raiffeisen Bank, Swarovski and UniCredit.

Study your passion

Core courses

The core courses cover coding, statistics, machine learning, data science, big data and cloud computing, and data engineering.

Sample courses

• Coding: Data Management and Analysis with R
• Coding: Data Management and Analysis with Python
• Coding Practice with R
• Data Analysis: Exploration – Business Analytics track
• Data Analysis 2: Finding Patterns with Regressions – Business Analytics track
• Data Analysis: Prediction and Introduction to Machine Learning
• Data Analysis: Causal Analysis
• Data Science: Machine Learning Concepts
• Data Science: Machine Learning Tools
• Data Visualization: Introduction to Data Visualization with Tableau
• Ethics of Big Data
• Data Engineering: SQL for Analysts
• Data Engineering: Different Shapes of Data
• Data Engineering: Big Data and Cloud Computing

Electives

Deepen your knowledge in analytics and engineering, or take up management and business courses.

Capstone Project

The final capstone project puts your applied skills to the test by matching you with an industry partner and exposes you to a complete analytics workflow. Use the full spectrum of skills you have acquired, challenge yourself, and generate valuable content for the partner. Past projects include designing a data warehouse, building a predictive model of customer behavior, fraud detection, and designing and evaluating experiments through data analysis.

Apply

Admissions requirements:

• Completed online application form
• Proof of English proficiency
• Letters of recommendation
• CV
• Bachelor’s degree
• Academic records
• Statement of purpose
• GMAT or GRE General Test or CEU Math Test
• Admission interview

Application deadlines:

• February 1, 2025 for master’s and PhD studies with financial aid
• March 15, 2025 for self-financing master’s candidates who will require a study visa
• August 15, 2024 for self-financing master’s candidates who will not require a study visa