91福利社

Course Details

Specialist Diploma in Data Science (Data Analytics)

Overview

  • Course Date:

    21 Oct 2025 to 31 Mar 2026

  • Registration Period:

    1 Jun 2025 to 31 Aug 2025

  • Duration/Frequency:

    2 evenings per week, 6.30 - 9.30pm

  • Mode of Training:

    Classroom

Please note that once the maximum class size is reached, online registration will be closed. You may register your interest and be notified when there is a new run.

Class schedule:
Tue, Thu evenings
6:30pm - 9:30pm

Modules in this course conduct in-class tests, typically in the last week of each 7-week or 8-week term in the 91福利社 academic calendar. Attendance at these tests are compulsory. 

Students are strongly advised against scheduling any travel plans during mid-semestral (MST) or end-semestral (EST) weeks. Detailed information regarding test schedules can be found on the website.

Course Duration: 

240 hours (1 year)

Please refer to the Academic Calendar.

Enquiries
Please email to ptenquiry@sp.edu.sg

Course Objective

Data is ubiquitous in government and in industry sectors including banking, insurance, healthcare, telecommunications, manufacturing, and retail. This course provides graduates with fundamental skills in statistics and data mining that are required by jobs in these industries that involve working with data and extracting information that is useful to businesses.

The objectives of the Specialist Diploma in Data Science (Data Analytics) are to provide training in the fundamentals of statistics and programming for data science, and to provide training on specialised skills in the areas of data mining and applied statistical methods. Graduates of the course will be competent in summarising and presenting data, performing statistical analysis of univariate and multivariate data, preparing data, developing and applying predictive models, and using descriptive models to uncover patterns in data.

More Information

This course consists of 2 post diploma certificates (PDCs). Each PDC comprises two modules and the details are as follows:

Please click  for the Module Synopsis.

Semester One
PDC 1 Certificate in Fundamentals of Data Science

  • Module 1 - Introduction to Statistics for Data Science
  • Module 2 - Introduction to Programming for Data Science

Semester Two
PDC 2 Certificate in Data Analytics

  • Module 3 - Data Mining Techniques
  • Module 4 - Applied Statistical Methods

Participants must complete PDC1 before they can progress to PDC2.

Broaden Your Horizons with Cross-Institution Recognition

Unlock greater flexibility and value through our cross-recognition partnership with Republic Polytechnic. 

By completing the Data Mining Techniques module from 91福利社's Specialist Diploma in Data Science (Data Analytics), you will be exempted from the Predictive Analytics with Machine Learning module in RP's Specialist Diploma in Business Analytics.

This cross-institution recognition empowers you to expand your learning pathways and career possibilities.

Other Exemptions

Upon completion of the Specialist Diploma, you may also receive:

  • An exemption of up to 12 subject credits for . 
  • An exemption for 2 modules, namely Data Programming in Python and Data Visualisation, for , awarded by UOL.
  • Module exemption for , subject to satisfactory performance. Suitable graduates will enjoy a waiver for the MTech EBAC Graduate Certificate modules of Statistics Bootcamp II and Statistics for Business II. The waiver will apply to all suitable graduates of the Specialist Diploma in Data Science (Data Analytics) programme from October 2021 onwards.

PDC Exemptions for Specialist Diplomas in Data Science

Participants who have graduated from this course may be eligible for PDC1 exemption if they plan to register for another Specialist Diploma in Data Science: 

Please note exemptions are evaluated on a case-by-case basis. Interested participants may email ptenquiry@sp.edu.sg. Our team will get in touch to address your queries and guide you through a separate application process. 

Course Fee

For more information on course fee / or to apply, click on the 鈥淩egister鈥� button.

Course fees are reviewed periodically and adjusted as necessary to cover the cost of education and to enable the polytechnic to continue investing in delivering high-quality education.

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Last updated: 11 June 2025

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