Nanyang Technological University (NTU)

Master of Science in Data Science (MSDS)

Data science is a data-driven approach to problem solving and scientific exploration that involves the process of collecting, managing, analyzing, explaining, and visualizing data and analysis results. It is inherently interdisciplinary in nature. The aim of the Master of Science in Data Science (MSDS) programme is to provide graduate students with robust training in the field of Data Science. The program is led and mainly run by the College of Computing and Data Science (CCDS). Faculty members from several other schools also actively contributes to this programme to support interdisciplinary flavour of data science.

The unique features of the MSDS program are as follows:

• Tight integration of relevant theories and principles from social sciences with computing-driven data science. Given that data is generated by humans or machines, it is paramount to consider social context for any data science problem. Consequently, the core courses focus not only on computing-driven data science courses but also courses and projects that steer students to take a realistic look at a data science problem by considering various social, economics, and behavioural issues. A wide range of elective courses to tackle various data types one may encounter in different application domains along with deeper insights to psychology and economic theories are provided to broaden the knowledge.
• Comprehensive coverage of the data science ecosystem. In MSDS program, we do not just simply teach analytics. Data analytics techniques are ineffective if your input data is dirty, messy, and not ready for analysis! Our program ensures every student goes through the entire data science ecosystem – from data preparation to data visualization, giving them a comprehensive depth and breadth of data science.
• The Capstone Project gives students hands-on opportunities to realize the data science ecosystem for domain-specific applications in industrial settings or academia. The former enables a student to address industry-specific data science problem whereas the latter allows a student opportunity to address such problem for non-industrial end users.
• Inter-disciplinary nature of MSDS is supported by courses taught by faculty members from different schools. In particular, the core course entitled “Data Science Thinking” will be jointly taught by faculty members from the School of Social Sciences (SSS) and CCDS. Several electives are also taught by faculty members of SSS and the School of Physical and Mathematical Sciences (SPMS). Furthermore, students may take an application domain-specific elective that may be offered by any school (e.g., NBS, SBS, ASE, MAE, EEE, SPMS, SSS, LKC) in NTU (excluding CCDS). Lastly, a capstone project in the MSDS program can be a collaboration between domain-specific industry participants, faculty members from various schools and CCDS.