SMU School of Economics launches second major in Data Science & Analytics

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The increasing volume of data and advanced data technologies pose new opportunities as well as challenges for data analysts to transform data to useful information for decision making. It is predicted that there would be a significant shortage of skilful workforce related to data analysis in Singapore.

SMU’s second major in Data Science and Analytics will equip graduates with the necessary tools and techniques to make an immediate impact, helping their employers navigate, process and derive insights from their data. Further, the program aims to provide graduates with an understanding of the rationale behind the techniques they are employing, enabling them to make informed and responsible choices as they assist organisations to navigate this new frontier.

A new second major in Data Science and Analytics will be launched by SMU School of Economics and is open to students from all SMU schools. The first targeted batch of students are all first-year students from the intake year of AY2019/-2020 and all second-year students from the intake of AY2018-2019.

This new major aims to train students with the ability to transform large amount of data into useful information for decision-making in an increasingly data-driven world.

Students taking the DSA second major will learn practical applications of statistical modelling, computing and information technology. DSA will equip students with up-to-date R* programming skills in data extraction, data cleansing, statistical analysis, predictive modelling and data visualisation.

Compulsory courses include: Statistical Learning with R; Data Science with R; Computational Thinking.

Electives include: Financial Data Analysis; Spatial Data Analysis; Big Data Analytics; Text Mining and Language Processing; Data Mining and Business Analytics; Introduction to Artificial Intelligence; Introduction to Machine Learning.

The outcome is graduates who will be adept and equipped with the knowhow to deploy applications of statistical modelling, computing and information technology as well as predictive approaches to solve problems encountered in all private and public institutions.  The curriculum of the DSA major adopts a hands-on pedagogy in both statistics and computational science, focusing on practical applications related to economics, social sciences, finance, risk management, business and insurance.

Andy Goldin, Data & Analytics Director, PwC South East Asia Consulting, said,In 2019 the ability to conduct analytics at scale is necessary for organisations to innovate and stay competitive. A company’s capability to process voluminous data sources and translate them into actionable insights allows for better, faster and smarter decision making. Investment in this area is at new heights, and with the advent of Artificial Intelligence, insights are becoming more accessible but less well understood.”

*R is one of the most popular open source software packages for statistical analysis. Data scientists and statisticians use and develop R programming language for data analysis in many fields. R users help to add new features to tackle new statistical issues every day, and encourage different domains of experts to work together by communicating in the R programming language.