Predictive Analytics is about discovering hidden patterns in data and making predictive outcomes using sophisticated statistical models and machine learning algorithms. While there are many GUI-based tools available, many data scientists still prefer to use programming languages for doing these advanced analytics due to the low set-up cost, huge flexibility to implement their desired functionalities and the support of broad user communities.
This course covers concepts, methodology, techniques and applications of predictive analytics using an open-source programming language. Several popular techniques such as cluster analysis, association analysis and decision trees will be introduced. There will be guided programming and participants will learn to perform data analyses and make decisions based on the analysis results.
|Intake Info||Application Closing Date||Course Duration|
(9 AM - 5:30 PM)
|Fee Type Item||Course Fees
|Full Course Fee||S$481.50|
|SG Citizens aged 39 & below / Permanent Residents||S$144.45|
|SG Citizens aged 40 & above / SME-sponsored SG Citizens & Permanent Residents||S$54.45|
SkillsFuture Credit Approved. For more details, please click here.
With effect from 1 Jul 2020, the Workforce Training Scheme (WTS) will be replaced by Work Support Scheme (WSS), for more information, please visit:
The course will be conducted by Lecturers of Temasek Polytechnic School of Informatics & IT who are specialists in the topics covered and are equipped with an expanse of experience in training practitioners in the industry.
- 67881212 (Mondays – Fridays, 9.00am – 5.00pm)
8.30am – 6.00pm (Mon – Thu)
8.30am – 5.30pm (Fri)
Closed on Sat, Sun & Public Holidays
Due to Safe Management Measures, our office is currently closed.
Please call or email us your enquiry.
Thank you for your patience and understanding.
- Website: https://www.tp.edu.sg/tsa
Temasek SkillsFuture Academy
East Wing Block 1A,
Level 3, Unit 81
21 Tampines Ave 1
Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel a course with low enrolment.