Specialist Diploma in Data Science (Data Analytics)

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Specialist Diploma in Data Science (Data Analytics)

Overview

Course Date:
21 Apr 2025 to 31 Mar 2026
Registration Period:
01 Dec 2024 to 31 Jan 2025
Duration/Frequency:
TBA
Mode of Training:
Facilitated Learning (Face-to-Face/ Online Synchronous) and Asynchronous E-Learning
Venue:
Singapore Polytechnic (facilitated classroom training) and Online E-Learning
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:
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 SP academic calendar. Attendance at these tests are 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
Email: 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 the business.

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.

Course Outline

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

Click here for Module Synopses

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.

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

Students enrolled in the Specialist Diploma in Data Science (Data Analytics) 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 who do not meet 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. Eligible applicants who are shortlisted 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 (Data Analytics) graduates will receive an exemption of up to 12 subject credits on SUTD’s Modular Masters in Data Science programme. Details can be found in SUTD website (https://www.sutd.edu.sg/Education/Academy/Our-Offerings/ModularMasters/ModularMasters-in-Data-Science)

Specialist Diploma in Data Science (Data 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 (Data Analytics) graduates will 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 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.

Suitable for

This course is suitable for working adults employed in sectors that require expertise in Data Science such as government, banking, insurance, telecommunications, manufacturing, and retail. The course contains a mix of theory and application, and requires that students have a good foundation in mathematics.

Special Requirements

Students in this course are required to bring a notebook computer to class. Necessary software is provided free-of-charge to students for the duration of the course.