COURSE OBJECTIVES
This course introduces essential numerical methods to students who are interested in data analytics and financial engineering. Major topics of the course include
- Introduction to supervised/unsupervised learning, including Kernel methods, support vector machines, K-means clustering, neural networks;
- Numerical methods for financial engineering with a focus on Monte Carlo methods importance sampling, and various variance reductions techniques.
Applications of these methods to practical problems arising from data analytics and financial engineering (e.g. option pricing) will be discussed. These methods also find many applications in various scientific fields, so students interested in scientific computing will benefit from this course as well.
PROGRAMME HIGHLIGHTS
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| Welcome message from Dean of NUS SCALE |
Tutorials conducted over Zoom
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Who Should Attend
Undergraduate students majoring in mathematics and other disciplines in science.
Pre-Requisites
Participants should have basic understanding of Calculus, linear algebra, probability theory at undergraduate level.
Participants should be able to read, write and communicate fluently in English, and understand basic terminologies used in the class.
Programme Schedule
For programme enquiries, please fill the form
hereMode of Delivery
15 hours of face-to-face teaching sessions including tutorials and final presentation.
Mode of Assessment
Students will be assessed via a variety of assignments and assessments:
Frequently Asked Questions
Q: What’s the tool/platform used during programme?
A: Participants are required to bring their own laptop (WindowsOS/MacOS/Linux), and install MATLAB before coming to the programme.
Q: What’s the estimated amount of self-study/preparation time outside the classroom?
A: Around 2 - 3 hours each day, which includes reviewing the material covered in class, and preparing for the presentation.
COURSE INSTRUCTORS
Below are the faculty members who have developed the course, and taught the programme in the past (names are arranged in alphabetical order):
Professor Weiqing Ren
Dept of Mathematics
Faculty of Science
National University of Singapore
Prof. Ren obtained his PhD from the Courant Institute at New York University in 2002. Before joining the National University of Singapore (NUS) in 2011, he was a member at the Institute for Advanced Study at Princeton (2002-2003), an instructor at Princeton University (2003-2005), and an assistant professor at Courant Institute (2005-2011). He is currently a Professor of Mathematics at NUS.
Prof. Ren received the Alfred P. Sloan Research Fellowship in 2007 and the Feng Kang Prize of Scientific Computing in 2015.Prof. Ren's research interest lies in the broad area of applied mathematics and scientific computing. His recent work has focused on:
- Building the mathematical foundation and finding effective numerical methods for modeling rare events (the string method, the minimum action method, etc),
- Modeling and simulation of multi-phase flows, in particular, the moving contact line problem,
- Development and analysis of multiscale, multi-physics numerical methods.
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CERTIFICATE OF COMPLETION
Successful participants who fulfill all program requirements, including meeting the minimum attendance and passing the assessment, will be awarded an e-Certificate of Completion and Assessment Report issued by NUS SCALE.
Certificate of Completion
A sample of the Certificate of Completion.
Assessment Report
A sample of the Assessment report.
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COMMENDATION LETTER
Participants from the project team with the highest score for the group project will also receive a commendation letter.
Commendation Letter
A sample of the Commendation Letter.
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SPEAK TO US
For enquiries, do contact us at sgprogrammes@nus.edu.sg should you have any questions regarding this programme.
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