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Predicting Risk Using Machine Learning


13 to 14 June 2018


9.00 am to 5.00 pm


Data Analytics Consulting Centre
Department of Statistics and Applied Probability
Computer Laboratory 2 (S16-05-102)
Faculty of Science
6 Science Drive 2
Singapore 117546


With the advancement of technology and Big Data, businesses are building more complex techniques and algorithms to identify risk. Using machine learning techniques, businesses are now able to build risk models which enable them to identify the likelihood and probability of customers being a risk. Businesses can therefore make smarter decisions in a timely manner.

Who Should Attend?

If you are required to apply analytics and machine learning techniques for improved business processes and decision-making, this course is for you!

• Data analysts 
• Data engineers 
• Data managers 
• Data scientists 
• Domain experts involved in business analytics projects 
• Financial analysts
• Machine learning scientists 
• Risk modelling analysts 
• Statisticians
• Technology professionals

This hands-on course uses Python programming language for building risk models. Participants should be familiar with computers and basic statistics.


Participants will acquire the following skills at the end of the course:

Applying machine learning techniques to identify high risk customers

Determining the probability of a customer being of high risk

Running a machine learning algorithm using Python programming language

Understanding the factors that may influence risk

Understanding the power of machine learning and its impact on business

Understanding how to evaluate and interpret risk model outcomes


This includes course materials, lunch and tea breaks.


$ 1,500
(excluding GST) 
  • Before 9 June 2018

Participants who complete the workshop will be awarded a Certificate of Participation.

NUS Faculty of Science reserves the right to postpone or cancel the workshop by giving 28 days notice prior to the start of the workshop.

    • Cancellation before or on 28 February 2018: Full fee refund

    • Cancellation between 1 to 28 March 2018: 50% fee refund

    • Cancellation after 28 March 2018: No refund


The course will cover the following topics:

• Overview of machine learning
• Importance of machine learning
• Impact of machine learning on businesses
• Types of machine learning techniques
• Linear Regression method
• Decision Tree method

The course will include hands-on practicals on the application of Regression Models and Decision Trees.


Prof Carol Hargreaves

Director, Data Analytics Consulting Centre
Faculty of Science, National University of Singapore

Prof Hargreaves is an analytics and business intelligence professional with over 28 years’ analytics experience. She has held leading roles in the pharmaceutical, healthcare, fast moving consumer goods and education industries.

Prof Hargreaves has worked with various leading companies to make businesses more intelligent. These include Pfizer, Novartis, MSD, Nestlè, MasterFoods, Goodman Fielder, Foxtel, Aztec (acquired by IRI), Cegedim Strategic Data (acquired by Quintiles IMS), the National Health and Medical Research Council and the National University of Singapore. Prof Hargreaves’ role includes analytics training, designing of analytics courses, and providing analytics advisory and consulting services. She is also a noted keynote conference speaker.

Prof Hargreaves has a passion for solving business problems using analytics and machine learning techniques to build data-driven solutions. Through faster and smarter business processes, her clients are empowered for organic revenue growth and to make effective decisions.




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Data Analytics Consulting Centre Block S16, Level 7
6 Science Drive 2
Faculty of Science
National University of Singapore Singapore 117546

Business Hours 
Monday to Thursday:
8.30 am – 6.00 pm
8.30 am – 5.30 pm