This course is eligible for SkillsFuture Singapore (SSG) funding.
Course Reference No: TGS-2020513530
In the present digital age, we encounter a variety of practical data science applications in our day-today activities. Many such applications have their foundations in relatively elementary mathematical concepts. As a mathematics educator, you may wish to complement the national efforts in digitalisation by becoming more effective in motivating data science applications of the subject and facilitating authentic learning related to data science among mathematics learners.
In this course, participants will be introduced to data science applications in such domains as commerce, education, finance, health and services, and the connections between the associated analytical techniques and topics in Mathematics will be elucidated. The topics include: functions, graphs, vectors, differentiation, probability, hypothesis testing, correlation and linear regression. Participants will also gain hands-on experience in data exploration and the development of a data-science deliverable for educational purposes.
Learning outcomes:
Outline
Session 1: Introductory data science
In this workshop, the attendees are introduced to data science concepts that will be useful when they design and develop their data science deliverables. They will get acquainted with common data science terms (artificial intelligence, machine learning, neural networks, etc.) and understand what they are about. There will be a short hands-on session with the R programming language, a popular tool for data science. No programming prerequisite is required. Attendees will be directed to other essential data science tools: Tableau, online resources for data, etc. Finally, we will go through examples of how simple mathematical concepts are being applied in data science.
| Applications | Mathematics Used |
| Neural Network – classification | Various concepts use: (i) linear algebra – z = wTx + b, (ii) functions: y = f(x), (iii) gradient descent – derivatives |
| Residential home price (Real Estate) Demand forecasting (Business) Analyze effect of treatments (Medical, Pharmaceutical) Stock price (Finance) |
Mainly linear regression, which uses: (i) least squares – differentiation, (ii) solving linear systems, (iii) Normal distribution |
| Anti-spam filters Automated medical diagnosis Instant loan approvals online TelCos – churning intervention |
k-nearest neighbor classification, which uses: (i) functions: y = f(x), (ii) Euclidean distances |
| Recommendation Systems – products (Amazon, Lazada), movies (Netflix), news articles (blogs, YouTube) |
Utility matrices – measuring similarity using the dot product |
Session 2: Data science activities
In this interactive practical, the attendees work through data science activities such as gathering data, applying models, interpreting results and refining models. These activities demonstrate the application of mathematical topics and provide attendees with ideas for their deliverables.
After this session, the attendees will work in groups to design and develop their data science deliverables under the guidance of the course facilitator. The deliverable can be a lesson/activity plan in the following form:
• Duration of activity
• Learning outcomes
• Sequence: What is the question? Where to get data? What concepts and tools are needed? What software should be used? How can the results be interpreted?
• Alternatives/Variations to consider
Session 3: Data science deliverables
The course culminates in group presentations, with discussions (highlighting, fine-tuning and consolidating best practices from various groups), of data science deliverables, which the attendees may use during the course of their work. Attendees will thus gain practical experience with acquiring & cleaning data, exploring and visualizing data, making predictions using the data, as well as exploring proposed models or hypotheses about the data.
Who Should Attend
Mode of Training
On-campus or Online (Live)
Instructor Profiles
Dr David Chew
Dr David Chew is assistant head and senior lecturer at the Department of Statistics & Data Science, NUS. After completing undergraduate and graduate studies in NUS, he spent two years in sunny University of Southern California (Go Trojans!) doing his post-doctoral training, before returning to join the department. He is currently the course coordinator of a massive data literacy general education module in the university. He is constantly experimenting with using technology to enhance teaching, and has offered his classes in a blended-learning format.
Course Date / Duration / Venue
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| Dates | Duration | Venue | Course Calendar |
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To be scheduled |
3 Days, 2.00pm to 5.00pm | Face-to-Face, National University of Singapore (S16) |
*Please note that registration will be closed 2 weeks before the course start date, or when registrations have reached full capacity, whichever earlier.
*The mode of delivery is subject to change.
Course Fee
| International Participant | Singapore Citizen1 39 years old or younger | Singapore Citizen1 40 years or older eligible for MCES2 | Singapore PRs | Enhanced Training Support for SMEs3 | |
| Full Programme Fee | S$1,350.00 | S$1,350.00 | S$1,350.00 | S$1,350.00 | S$1,350.00 |
| SkillsFuture Funding (Refer to Funding Page for Claim Period) |
– |
(S$945.00) | (S$945.00) | (S$945.00) | (S$945.00) |
| Nett Programme Fee | S$1,350.00 | S$405.00 | S$405.00 | S$405.00 | S$405.00 |
| 9% GST on Nett Programme Fee | S$121.50 | S$36.45 | S$36.45 | S$36.45 | S$36.45 |
| Total Nett Programme Fee, Incl. GST | S$1,471.50 | S$441.45 | S$441.45 | S$441.45 | S$441.45 |
| Less Additional Funding if Eligible Under Various Scheme | – | – | (S$270.00) | – | (S$270.00) |
| Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes | S$1,471.50 | S$441.45 | S$171.45 | S$441.45 | S$171.45 |
Course Application
You can register for the available short courses via NUS Online Application Portal.
Self-registration guide for Short Courses & Professional Certificates
Contact Us
Who can I contact for further clarifications/assistance?
For all Short Courses and Professional Certificates related, please email us at fos.shortcourses@nus.edu.sg .
FAQ
Course Registration
Registration will close two weeks before commencement date or when the class is full, whichever earlier. If you wish to register after the registration closes, please email us and we may review on a case-by-case basis.
An acknowledgement email will be sent to you.
No. The acknowledgment email is to inform you that the registration is submitted successfully. Your registration is still required to be processed by the short course coordinator internally. Should you have any queries pertaining to your registration, or have any changes to be made, please email us.
You may register via NUS Online Application Portal and select “NUS Alumnus (with R&G voucher)”. Follow the login instructions.
The short course coordinator must be notified in writing of all requests for withdrawals and deferment at least 7 days before the run.
If you have accepted the offer to a short course programme run, but find that you are unable to attend, you should notify us by writing to fos.shortcourses@nus.edu.sg .
Applicants may postpone participation and request for deferment to other course runs, subject to availability.
Requests for cancellation will be considered on a case-by-case basis, and refunds may be issued.
Please note that we are unable to process any refunds for NUS Alumni utilising R&G vouchers. More information on R&G Voucher can be found here.
Course Funding
Please refer to the ‘Course Fees’ section in the course brochure.
Yes. All Singapore Citizen/SPR attending SSG funded courses will be eligible for SSG Funding, provided you have not taken the same course before.
In addition, you must meet the two criteria:
The course fees will automatically be tabulated with the relevant SSG funding based on your eligibility. No action is required from the participant/company except to ensure that the participant meets the two criteria stated above.
Yes. Once an offer of placement has been granted for your application, you will have to accept the offer via NUS Online Application Portal and make the payment via your SkillsFuture credits. Payment is not required upfront during registration.
Payment
Once your registration has been processed and an offer of placement has been granted to you, you will receive an automated email for you to accept the offer on NUS Online Application Portal.
Once you have accepted the offer, you will be directed to the payment page.
Yes, you are still required to login and accept the offer. Otherwise, your placement may be withdrawn.
Your R&G voucher will be deemed used once you accept the offer. No refunds will be made for any redeemed voucher.
Assessment
Yes. The mode of assessment is up to the CET instructor’s discretion. It may be a reflection paper, quiz, presentation, or based on classroom activities. You will be required to achieve a ‘Competent’ grade for the assessment(s).
You will be notified by the short course coordinator if you did not achieve “Competent” for the short course. You may be offered for a deferment for the next available class.
E-Certificate
An e-certificate will be issued upon successful completion within 20 working days.
The name on the e-certificate will be issued according to the full name as per registration.