البرامج التنفيذية

Message from dean

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The HBKU 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 the students with state-of-the-art methods and theory related to the next generation of Big Data technology.The program offers its students the option of either completing a research thesis, or working on an industrial project. The thesis requires substantial theoretical and research components while the industrial project offers a route for students to further develop real-world, practical, problem-solving experience.The program includes a core course in leadership and innovation, highlighting an emphasis within the program of producing graduates equipped with the skills and knowledge to take on leading roles within academic, governmental and non-governmental organizations.

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