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.
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Requirements
Minimum hours required to complete program 33 CH
Course List
| Code |
Title |
Hours |
| CSE 602 | Statistics for Science and Engineering | 3 |
| DSEG 733 | Advanced Data Management System | 3 |
| ICT 601 | Research Methods and Ethics | 3 |
| ICT 705 | Applied Data Analytics | 3 |
| 12 |
| 12 |
| |
| Convex Optimization for Large-Scale and Distributed Systems | |
| Advanced Algorithms and Data Structures | |
| Principles of Computer System Design | |
| Wireless Networks & Security | |
| Applied Deep Learning | |
| Special Topics in Data Science and Engineering | |
| Learning from Data | |
| Machine Learning | |
| AI for Social Media and Multimedia Applications | |
| Computer Graphics | |
| Advanced Applications of the Web and Internet | |
| Principles of Health Informatics | |
| Artificial Intelligence and Machine Learning in Healthcare | |
| Computational Bioinformatics | |
| Medical Image Processing | |
| Special Topics | |
| Independent Studies | |
| Data Science Tools and Applications | |
| Cloud Computing | |
| Quantum Computing | |
| Interactive Design for Health care | |
| 12 |
| |
| ICT 701 | Graduate Research Seminars | 0 |
| 0 |
| |
| Master's Thesis Hours | |
| Industrial/ Project (+ One elective from list above) | |
| 9 |
| | 0 |
