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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 multidisciplinary in nature. Despite its growing importance in today’s world, our ability to leverage and exploit data has been limited by the lack of knowledge exchange between experts in the sub-fields of data science, and by the lack of tools, methods, and principles for understanding and translating these insights into products, systems, and policies. NTU’s Data Science aims to address this chasm by providing robust education, research, and training on various facets of the Data Science ecosystem.

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We live in a data-driven world. We are generating, collecting, and storing data at an unprecedented rate. However, existence of such massive data may not necessarily translate to positive transformation to businesses, sciences, as well as everyday life. It is paramount to be able to make sense of the data by moving the needle from simply collecting massive raw data to actionable data-based and data-driven insights that can bring about necessary and feasible transformation to business and society. Data Science plays a central role towards this goal.  Particularly, Data Science have a synergistic relationship with Artificial Intelligence (AI) – robust and effective Data Science techniques and frameworks pave the way for “good” AI and superior AI techniques may enable “good” Data Science.

 

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Constructing large and complex data science pipelines to address needs in a wide variety of application domains (e.g., finance, manufacturing, biology, economics) is a critical challenge in today’s world. The suite of Data Science programmes in NTU at various levels are designed for students who wish to develop, design and implement data science systems and to garner deep understanding of data science for management and setting policy. They emphasize on data science ecosystem, techniques and tools to solve real world data-science related problems in various application domains. A hallmark of some of the programs is tight integration of relevant theories and principles from social sciences with computing-driven data science. Given that data is often generated by humans or related to humans (e.g., social data, surveillance data), it is paramount to consider social context for any data science problem. Consequently, NTU’s data science programmes offer courses focusing not only on computing-driven data science courses such as data preparation, data management, machine learning, and data visualization but also courses and projects that steer students to take a realistic look at a data science problem by considering various social, economical, and behavioural issues.