Specialist Diploma in Data Science (Predictive Analytics)

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Specialist Diploma in Data Science (Predictive Analytics)

Overview

Course Date:
21 Apr 2025 to 31 Mar 2026
Registration Period:
01 Dec 2024 to 02 Mar 2025
Duration/Frequency:
2-3 evening per week, 6.30pm-9.30pm
Mode of Training:
Classroom
Venue:
Singapore Polytechnic
Funding:
Eligible for SkillsFuture Credit

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

Class schedule:

PDC1 (1^st semester):

Every Tue and Thu

6:3pm – 9:30pm (face-to-face class)

9:30pm – 10:30pm (e-learning*)

PDC2 (2^nd semester):

Every Wed 7:30pm – 8:30pm (online class**)

Every Thu 6:30pm – 9:30pm (face-to-face class)

Every Sat 9:00am – 1:00pm (e-learning*)

*e-learning: the students are not required to attend classes during this period.

**online class: the students may attend from any location of their choice.

Modules in this course conduct in-class tests, typically in the last week of each 7-week or 8-week term in the SP academic calendar. Attendance at these tests is compulsory. Please refer to the SP academic calendar.

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 Academic Calendar.

Enquiries
For enquiries, please email to ptenquiry@sp.edu.sg

Course Objective

Requirement to gather, analyse, prepare, and model Data, of varied structures, is prevalent in the modern-day industrial setting. Banking, Finance, Insurance, Healthcare, Telecommunications, Design, Manufacturing, and Retail are some of the many affected industries requiring to skilfully produce accurate information. Hence, this course provides fundamental skills in Statistical Analysis and Predictive Analytics to related professionals, involved in processing data to valuable Business insights.

Participants will undergo foundational training in the fundamental concepts and methods of Data Science Statistics and Programming, as well as in specialised skill sets in the area of Statistical Modelling and Prediction. Graduates will be competent in preparing data, performing statistical analysis, building and deploying predictive models, as well as quantifying risks associated with the prediction.

Course Outline

The course is a one-year part-time programme. It consists of 2 Post Diploma Certificates (PDCs) conducted over 2 semesters, 1 PDC per semester. PDC1 starts first, and classes are conducted in the evening.

This course consists of 2 PDCs. Each comprises two modules and their details are as follows:

Please click here for 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 Predictive Analytics
Module 3 - Modelling Fundamentals & Statistical Learning
Module 4 - Machine Learning & Predictive Modelling

Participants must complete PDC1 before they can progress to PDC2.

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.

Minimum Requirements

Must satisfy at least one of the following entry requirements:

(i) An Engineering diploma from a polytechnic in Singapore
(ii) Any diploma or degree from a polytechnic* or university** in Singapore AND

a C6 or better in Additional Mathematics in the O-level examinations; or
a pass in H2 Mathematics in the A-level examinations; or
a C grade or better in a one-semester Mathematics module that substantially covers the Additional Mathematics syllabus; or
relevant work experience (considered on a case-by-case basis)

* NYP, NP, RP, SP, or TP
** NTU, NUS, SIT, SMU, SUSS, or SUTD (candidates with degrees from other universities are considered on a case-by-case basis)

Recognition of Prior Learning

Applicants, not meeting the entry requirements, may apply for admission to the course by producing evidence of at least 5 years relevant working experience or supporting information to ascertain their competency readiness. Shortlisted applicants may have to go through an interview and/or entrance test.

The Polytechnic reserves the right to shortlist eligible applicants and admit applicants who perform well in the interview and/or entrance test

Certification / Accreditation

Upon completion of two Certificates within a two-year validity period, the participant will be conferred a Specialist Diploma qualification from Singapore Polytechnic.

Specialist Diploma in Data Science (Predictive Analytics) graduates will receive an exemption of up to 12 subject credits on SUTD’s Modular Master's in Data Science programme. Details can be found in SUTD website ModularMaster in Data Science - Singapore University of Technology and Design (SUTD).

Specialist Diploma in Data Science (Predictive Analytics) graduates will receive exemption 2 modules, namely Data Programming in Python and Data Visualisation from UOL MSc in Data Science and Artificial Intelligence. Details can be found in SIM website UOL MSc in Data Science and Artificial Intelligence | SIM GE

Specialist Diploma in Data Science (Predictive Analytics) graduates will also receive module exemption for NUS-ISS’ Master of Technology in Enterprise Business Analytics (MTech EBAC) programme, subject to satisfactory performance. Suitable graduates will enjoy a waiver for the MTech EBAC Graduate Certificate modules of Statistics Bootcamp II and Predictive Analytics-Insights of Trends. The waiver will apply to them, from October 2021 onwards.

Suitable for

Working adults, employed in sectors requiring expertise in Data Science such as Government, Banking, Insurance, Telecommunications, Design, Manufacturing, and Retail. In particular, working adults, needing to be equipped with technical and practical Predictive Modelling skills to handle Data with a variety of structures, stand to benefit well from the course. Containing a mix of theory and application, participants are required to have a good foundation in mathematics.

Special Requirements

Participants in this course are required to bring notebook computers to class. Necessary software is provided free-of-charge for the duration of the course.