Master of Science in Data Science and Engineering
cse

Master of Science in Data Science and Engineering

A graduate program in the emerging field which addresses the growing need to utilize the massive amounts of unstructured data.

Hamad Bin Khalifa University

The Master of Science program in Data Science and Engineering aims to provide students with a strong foundation in data engineering, ‘big data’ science, and data analysis. The program integrates the knowledge, expertise and educational assets of HBKU and its research institutes in data collection, management and analytics, and scalable data-driven knowledge discovery, as well as the fundamental concepts behind these techniques.

The program aims to equip students with state-of-the- art methods and theory related to the next generation of ‘big data’ technology. It offers its participants the option of either completing a research thesis or working on an industrial project.


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, spanning areas such as applied statistics, machine learning, and technological tools such as cloud platforms for large-scale data analysis.
  • Hands-on experience in 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 CSE and from HBKU’s research institutes.

Curriculum

A 33-credit program, taught in English, typically over two years that includes:

  • Four 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
    • Advanced Data Management Systems
    • Computational Data Analytics & Tools
  • Four 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 engineering, and the interrelations between them.
  • Two semesters of graduate research seminars

    • Two semesters of graduate research seminars aimed at expanding students’ horizons by offering a broad range of topics covered through invited talks and presentations from industry, research institutes, academia, and government institutions and organizations.
  • Students are also recommended to take a machine learning course as an elective.

  • A nine-credit research thesis or six-credit industrial project.

  • The program offers flexibility by enabling students to focus on different areas of interest through the choice of electives and projects related to data science and engineering, such as data collection, storage, management, analysis, and knowledge extraction and discovery.

View Admission & Application Requirements