Introduction
The need to handle, prepare, analyse and model data of varied structures is prevalent in the modern day industrial setting including industry sectors such as banking and finance, insurance, healthcare, telecommunications, design and manufacturing, and retail. This course provides graduates with fundamental skills in statistical analysis and predictive analytics that are required by jobs that involve managing, analysing and modelling data and extracting information that is useful to the business.
Course Objectives
The objectives of the Specialist Diploma in Data Science (Predictive Analytics) are to provide foundational training in the fundamental concepts and methods of statistics and programming for data science, as well as in specialized skill sets in the area of statistical modelling and prediction. Graduates of the course will be competent in preparing data, performing statistical analysis, building and deploying predictive models and quantifying risks associated with the prediction.
Suitable for
This course is suitable for working adults employed in sectors that require expertise in Data Science such as government, banking, insurance, telecommunications, design and manufacturing, and retail. In particular, working adults who need 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. 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.
Minimum Entry Requirements
Applicants enrolled in the Specialist Diploma in Data Science (Predictive 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.
Course Outline
The course is a one-year part-time programme. It consists of 2 Post Diploma Certificates (PDC) conducted over 2 semesters, 1 PDC per semester. The first PDC to start with is PDC1. The classes are conducted in the evening.
This course consists of 2 post diploma certificates (PDCs). Each PDC comprises two modules and the 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 - Introduction to Statistical Modelling
Module 4 - Generalised Modelling and Forecasting
Participants must complete PDC1 before they can progress to PDC2.
Award / 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 18 subject credits on SUTD’s ModularMasters 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)
Course Fees
Click here for Funding Incentives and Fees Matters
| SPECIALIST DIPLOMA IN DATA SCIENCE (PREDICTIVE ANALYTICS) |
|---|
| POST DIPLOMA CERTIFICATES (PDC) | SINGAPORE CITIZENS BELOW THE AGE OF 40 | SINGAPORE CITIZENS AGED 40 AND ABOVE | SINGAPORE PR | ENHANCED TRAINING SUPPORT FOR SME SCHEME (for SC)* | ENHANCED TRAINING SUPPORT FOR SME SCHEME (for PR)** | OTHERS / REPEAT STUDENTS |
|---|
| Certificate in Fundamentals of Data Science | $437.20 | $291.47 | $1,165.87 | $301.00 | $348.67 | $2,914.68 |
| Certificate in Predictive Analytics | $437.20 | $291.47 | $1,165.87 | $301.00 | $348.67 | $2,914.68 |
| Total Course Fees: | $874.40 | $582.94 | $2,331.74 | $602.00 | $697.34 | $5,829.36 |
*SC - Singapore Citizens
**PR - Permanent Residents
Other Fees Payable:
| FEE DESCRIPTION | PER SEMESTER (AFTER GST) |
|---|
| | SINGAPORE CITIZENS | SINGAPORE PR AND OTHERS |
|---|
| Examination Fee | - | $16.05 |
| Miscellaneous Fee | $7.49 | $7.49 |
| Statutory Licence Fee (CLASS) | $1.01 | $1.01 |
| Insurance Fee (GPA) | $1.70 | $1.70 |
| Total | $10.20 | $26.25 |
- The fees shown (inclusive of 7% GST) are indicative as they are based on prevailing funding policies and subject to review.
- Post Diploma Module Certificate fee is payable on a semester basis.
Refund Policy:
- Withdraw within 2 weeks before semester commencement, 70% refund of paid course fee.
- Withdraw on or after date of semester commencement, no refund of paid course fee.
Please note that other fees paid are non-refundable.
Please click here for application procedure.
Course Commencement:
19 Apr 2021
Academic Calendar
Registration Period:
Registration closed
* Registration may be closed once seats are filled up
Class schedule:
Every Tue and Thu
5:30pm - 6:30pm (e-learning*)
6:30pm - 9:30pm (face-to-face class)
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.
*e-learning: the students are not required to attend classes during this period.
Duration:
240 hours (1 year)
Enquiries
Email: ptenquiry@sp.edu.sg
