Offering Skills for Business Analytics
The big data boom has brought about a shortage of data scientists and business analysts. Firms increasingly recognize the value of the huge amounts of data they produce, if such data are analyzed correctly and creatively. The skills needed to analyze and act upon data are dispersed among managers, economic analysts, computer scientists, statisticians and engineers. Business analytics, especially involving big data, can help firms make smarter and more effective decisions. Big data is a source of future growth, and a major trend that will play out over many years.
Coursework in an Interdisciplinary Program
Learn the full spectrum of knowledge and skills you need to create value from big data and other sources of quantitative information. Understand the management and economic aspects of how data creates value.
You will be familiar with all aspects of business analytics, including applications assisting business decision making. You will understand the pressing questions posed by managers, the methodological challenges of statistics, and the power and limitation of technologies. You will be sought for key positions, or may even become an entrepreneur in the booming analytics startup arena.
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 1.30pm. Some courses run with 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 you land a full-time job, you may request a change of status and become a part-time student.
Join part-time as a working professional. As a part-time student, you may request a second year to continue taking elective courses or to complete your Capstone Project. Please note that we cannot guarantee the location of elective courses in the second year (Budapest or Vienna).
The core courses cover coding, statistics, machine learning, data science, big data and cloud computing, and data engineering.
- In Fall term, foundation courses cover an introduction to R, statistical foundations, data management basics, and a review of open-source and commercial data science and big data tools. We also cover concepts of business intelligence, data visualization and storytelling.
- In Winter term, advanced courses cover prediction methods and machine learning, as well as practical and data engineering aspects of putting analytics into production. Use case courses help bring methods learned closer to real life experiences.
Deepen your knowledge in analytics and engineering, or take up management and business courses.
- In Winter term, electives cover advanced machine learning and data engineering, and Python as another language of data science.
- In Spring term, mastering courses tackle narrow topics such as deep learning and data science team and project management.
- Take further courses anywhere at CEU, from network science to environment and energy economics.
The final Capstone Project puts your applied skills to work by matching you with an industry partner. Its goal is to expose 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.