Masters

Information is the oil of the 21st century, and analytics is the combustion engine.

Peter SondergaardGartner Research

Program Focus

Fundamental knowledge in data science, engineering and technology covering important aspects and spanning areas such as applied statistics, machine learning, and technological tools such as cloud platforms for large-scale data analysis.

Hands-on experience on real-world projects related to scalable big data collection, storage, management, analysis and mining, as well as knowledge extraction and discovery.

Research thesis or industrial project involving original work related to data science and engineering guided by world-class faculty members from the College of Science and Engineering and from the HBKU Research Institutes.

Curriculum

A 37-credit program, taught in English, typically over 2 years that includes:

core courses that provide students coming from diverse backgrounds with a coherent learning environment to tackle issues in data science and engineering. The core courses are:
- Research Methods and Ethics
- Applied Statistics
- Machine Learning
- Computational Data Analytics & Tools
elective courses covering some engineering and science fundamentals in addition to a variety of data science and engineering electives, providing students with a solid base and depth to fully understand different aspects of data science and engineerin