Page 77 - Special Topic Session (STS) - Volume 3

STS515 Jeremiah D. D. et al.

Data Science programmes: Is there
an ideal design?
Jeremiah D. Deng, Matthew Parry
University of Otago, New Zealand.

Abstract
“Data Science" has become a buzzword in recent years, and many universities
have started offering undergraduate degrees in Data Science. Yet the shape
of Data Science as an interdisciplinary field remains elusive for a clear
definition, and the curriculum design varies from one programme to the other.
In this paper we sample a few Data Science undergraduate programes offered
in a number of institutes in the US, China, Australia, and New Zealand. The
diversity of these programmes is revealed by using indices quantified on four
dimensions: mathematical, statistical, computing, and programming.
Furthermore, we use Machine Learning as the core subject within a Data
Science programme in an effort to map out some key, prerequisite subjects as
required for teaching mainstream algorithms effectively. We also argue that
there are also other aspects of Data Science that can be easily neglected by
most offerings, such as distributed database systems, and privacy preserving
data mining, let alone domain-rooted subjects such as biomedicine and
computational finance. With these considerations in mind, we call for a flexible
curriculm design that incorporates a thin core and allows students to opt for
endorsements in different specialties, e.g. statistics, information technology,
and big data applications.

Keywords
Data science; curriculum design; diversity

1. Introduction
Data Science as an interdisciplinary subject has become an increasingly
important area that attracts intensive efforts worldwide in teaching, research
and development. As a relevant subject statistics as regained popularity and
the number of undergraduate statistics degrees have trippled over the last
decade largely due to the emergence of big data .
1
Having become a buzzword, “data science” still lacks a clear, widely
adopted definition. The very nature of data science, its content, and
perceptions regarding to its potentials and weakness etc., remain hot topics

The Conversation.com, “Statistics and data science degrees: Overhyped or the real deal?”,
1
URL https://theconversation.com/statistics-and-data-science-degrees-overhyped-or-the-real-
deal-102958, October 29, 2018. Retrieved April 30, 2019
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