Offering Skills for Business Analytics
The big data boom has brought about a shortage of data scientists and business analysts. Companies increasingly recognize the value of the huge amounts of data produced each day, indeed every minute and second, if such data are analyzed correctly and creatively. The skills needed to analyze and act upon insights from 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 will be a source of future growth and is a major trend that will play out over many years.
Coursework in an Interdisciplinary Program
The MS Business Analytics offers the full spectrum of knowledge and skills you need to create value from big data and other sources of quantitative information, while emphasizing the management and economic aspects of how data creates value.
You will be familiar with all aspects of business analytics with an emphasis on big data, including applications assisting business decision making. Understanding the pressing questions posed by managers, the methodological challenges of statistics, and the power and limitation of technologies, you will be sought for key organizational positions and may even become an entrepreneur in the booming analytics startup arena.
Study Full-time or Part-time
Study full-time (10 months) as a graduate or career changer
- Enter a job or internship at any time
- Land a job and switch from full-time to part-time.
Study part-time (22 months) to keep or upgrade your career
- Study once a week from 1.30-7.30pm
- Take some electives in evenings or weekends.
The core courses combine several disciplines. They 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. User case courses help bring methods learned closer to real life experiences.
Electives allow you to either 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.
- You can choose from courses offered with the MS in Technology Management and Innovation. You can take further courses anywhere at CEU, from network science to environment and energy economics.
For your final capstone project you are matched with an industry partner. The project's goal is to expose you to a complete analytics workflow with a variety of tasks at a company or other organization. You will use the full spectrum of skills you have acquired, challenge yourself, have a valuable learning experience, and generate valuable content for the partner. Past projects include designing a data warehouse in a large organization, building a predictive model of customer behavior, fraud detection, and designing and evaluating experiments through data analysis.