A Data-centric Computing Curriculum for a Data Science Major

ABSTRACTMany universities are introducing a new major in Data Science into their offering, to reflect the explosive growth in this field and the career opportunities it provides. As a field Data Science has elements from Computer Science and from Statistics, and curricula plans differ widely, both in the balance between the CS and Stats aspects, and also in the emphasis within the computing topics. This paper reports on the curriculum that has been taught for three years now at the University of Sydney. In particular, we describe the approach of a sequence of computing subjects which were developed specifically for the major, in order to bring students over several years to a sophisticated understanding of the data-handling aspects of Data Science. Students also take traditional subjects from both CS (such as Data Structures or AI) and from Statistics (such as Learning from Data and Statistical Inference). The data-centric specially-designed subjects we discuss in this paper are (i) Informatics: Data and Computation (in the first year), (ii) Big Data and Data Diversity (in the second year), and then upper-division subjects on (iii) Data Science Platforms, and (iv) Human-in-the-Loop Data Analytics.