Life as a Business Analytics student
Today's businesses run on data. From web analytics and accounting to market research and demographics, our information-centric world generates countless terabytes of data year after year. Data analysts play the increasingly important role of making sense of all that data.
As a Business Analytics student, you will gain a solid foundation in the statistical and analytical methods that make up the backbone of data science. You'll learn to work with spreadsheets, aggregate data, evaluate statistical significance, and determine statistical trends.
With a background in Business Analytics, you can find a niche in almost any industry. Data analysts can be found everywhere from IT consultancies to web marketing agencies, inside government bureaus and at leading startups.
An NUS education provides a strong technical foundation across all areas of computing, meaning that your Business Analytics training will be bolstered by strong general computer skills. Accordingly, a Business Analytics degree from NUS will provide you with the skills and expertise needed to build a career in today's fastest-growing and most exciting profession.
Learn big data and data mining techniques
Predict customer behaviour with analytics
Solve business problems with intelligent insights
Use A.I. to model business outcomes
Build expertise with a specialisation
Our Business Analytics programme offers three specialisations to give students the opportunity to build expertise for key job domains:
Gain the technical skills to pursue niche jobs in Investment, Banking, Finance, Trading, Mergers and Acquisitions, and Fund Management. Learn to effectively use the latest tools and systems for financial data modelling and metrics. Perform deep dive analytics for budgetary control, portfolio and fraud detection. Build a solid understanding in statistical modelling and methods for quantitative trading. With this specialisation, you will be able to simulate and automate trading, as well as analyse investments with risk-return trade-offs.
Gain a deep foundational knowledge and expertise in machine learning-based analytics and techniques. With this specialisation, you will develop and hone your machine learning (ML) (a sub-field of Artificial Intelligence or AI) skills and knowledge further, so as to be more ready to design and develop complex business analytic solutions involving ML analytics and techniques, and take on careers in the business/data analytics field in roles of AI/ML engineers, AI specialists, and AI applied researchers.
Learn to effectively use the latest tools and technologies to analyse marketing data and create intelligent insights on a business’ 4Ps (pricing, promotion, product, place) and 3Cs (customer, company, competitor). Develop the skills to use cutting edge technology to model marketing data and to create strategic marketing campaigns and promotions. Learn how to use analytics tools to draw insights on customer profiles and purchase patterns. Be equipped to take on career paths in a myriad of industries, from marketing, customer relationship, market research, to investment and product development.
Widen your horizon through a Double Major or Minor programme
Students can also apply to do a Double Major (e.g., in economics) or Minor (e.g., in Economics, Financial Mathematics, Information Security, Real Estate or Statistics). For further information, please refer to: http://www.nus.edu.sg/oam/programmes.html
View Course Curriculum for Regular Programme
Sampler of Modules
BT1101 Introduction to Business Analytics
Apply basic business analytics tools in a spreadsheet environment, and learn to communicate with analytics professionals to effectively use and interpret analytic models and results.
BT2101 Econometrics Modeling for Business Analytics
Learn predictive modelling techniques (e.g. regression, times series forecasting, dynamic casual effects modeling) to support evidence-based business decision making.
BT3102 Computational Methods for Business Analytics
Learn optimization methods, numerical analysis, simulations, monte-carlo methods, graph and flow methods, and computational complexity issues to address business analytics related problems.
BT4102 Fraud Analytics
Learn foundational application of analytics in the audit and investigation processes to address crimes like fraud, money laundering, market manipulation, cyber intrusion, and control lapses.
BT4211 Data-Driven Marketing
Study marketing metrics, data management, market response and diffusion models, market segmentation models, and digital media marketing analytics.
BT4221 Big Data Techniques and Technologies
Examine big data infrastructure, analytics scalability and processes, Hadoop, HBase, Cassandra, MapReduce, Dynamo, R, in-database analytics, and mining of data streams.
BT4222 Mining Web Data for Business Insights
Use text mining methodologies, web data mining for marketing, sales and finance applications, social web data mining from Facebook and Twitter, and web analytics involving clickstream and site traffic data.
BT4240 Machine Learning for Predictive Data Analytics
Study the endless insights available from social network analysis methods and tools, clustering and association techniques and business cases for social network platforms.
What You Could Be
Web Analyst at AC Nielsen
IT Business Analyst at Citibank Singapore Machine Learning Engineer at DBS Monetization Analyst at Facebook
Data Mining Specialist at Symantec
Market Research Analyst at Singtel
Business Analyst at Deloitte Analytics
Data Scientist at Singapore Press Holdings
Healthcare Analyst at Khoo Teck Puat Hospital, Alexandra Health System
View Course Curriculum for Regular Programme