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Data Science

Degree Type   Bachelor of Computer

Division   Natural and Applied Sciences

The field of Interdisciplinary Data Science (IDS) deals with the theories, methodologies and tools of applying statistical concepts and computational techniques to various data analysis problems related to science, engineering, medicine, business, etc. The objective is to inspect, clean, transform and model data in order to discover useful information, suggest conclusions and support decision-making. It is an emerging topic that plays a critical role in almost every discipline of today’s science and technology and has become an indispensable component.

Interdisciplinary data science is a highly interdisciplinary field. Its methodologies are mostly derived from statistics theories. The computational algorithms for implementing these statistical methodologies are based upon numerical computation and optimization, and are often executed on a large-scale hardware platform composed of massive computing units and storage devices. When applying data analysis to a specific application problem, it further requires disciplinary knowledge and expertise. To accomplish these ambitious goals, there is an immediate need to “invent” a radically new degree program that can break down the traditional boundaries between disciplines and, consequently, facilitate fundamental breakthroughs and innovations.

Requirements

Common Core

The field of Interdisciplinary Data Science (IDS) deals with the theories, methodologies and tools of applying statistical concepts and computational techniques to various data analysis problems related to science, engineering, medicine, business, etc. The objective is to inspect, clean, transform and model data in order to discover useful information, suggest conclusions and support decision-making. It is an emerging topic that plays a critical role in almost every discipline of today’s science and technology and has become an indispensable component.

Interdisciplinary data science is a highly interdisciplinary field. Its methodologies are mostly derived from statistics theories. The computational algorithms for implementing these statistical methodologies are based upon numerical computation and optimization, and are often executed on a large-scale hardware platform composed of massive computing units and storage devices. When applying data analysis to a specific application problem, it further requires disciplinary knowledge and expertise. To accomplish these ambitious goals, there is an immediate need to “invent” a radically new degree program that can break down the traditional boundaries between disciplines and, consequently, facilitate fundamental breakthroughs and innovations.

 
The three courses are:
  • China in the World, which focuses on the historical and contemporary commercial, intellectual, and scientific exchanges between China and multiple locations around the world.
  • Global Challenges in Science, Technology, and Health, which addresses key developments in fields such a biotechnology, nanotechnology, and information technology, highlights the global environmental challenges of our time, and teaches strategies for critically evaluating scientific claims.
  • Ethics, Citizenship and the Examined Life, which explores traditional Asian and Western ideals and contemporary analyses of moral self-cultivation, democracy and meritocracy, and pluralism and uniformity.

Divisional Foundation Courses

Option 1: only applicable to Class of 2022 who have taken INTGSCI 101 & 102

Option 2: only applicable to Class of 2022 who have taken INTGSCI 101

  • Introductory Calculus
  • Introductory Calculus
  • Introductory Calculus

Meet the Faculty