Every time you send a text message, type a tweet, post a Facebook photo, click a link, or buy something online, you are generating data. Considering that there are more than 3 billion Internet users in the world and 1.75 billion cell phone users, that is a whole lot of BIG DATA to collect, organize, and analyze.
Companies are increasingly looking for data masters who know how to turn these data into valuable business insights. Data engineers and data scientists are the two most sought-after professionals in big data projects. Data Engineers are the data specialists who prepare the “big data” infrastructure to be analyzed by Data Scientists. They are software engineers who design, build, integrate data from various resources, and manage big data. This course provides a headstart to graduates who want to become data engineers by equipping them with specialised skills to work with big data and real-time analytics.
The objectives of the Specialist Diploma in Data Science (Big Data and Streaming Analytics) are to provide students with the knowledge and skillsets to work with very large datasets and continuous streaming data which need to be processed in real-time. Students will gain hands-on experience with the technologies that enable the ingestion and management of Big Data and real-time data. These graduates would meet the demand of the increasing number of companies which need to collect, store and manipulate datasets that exceed thousands of terabytes and to process continuous data in real-time.
This course is suitable for working adults employed in sectors that require expertise in Data Engineering or Data Science such as government, banking, insurance, telecommunications, manufacturing, and retail. The course is a mix of theory and application, and is suitable for students who have prior experience or strong interest in the technical aspects of information technologies.
Participants are required to bring a personal laptop to class. The laptop must have the following specifications due to the requirements of software that used in this course:
- Windows 10 operating system with Intel i7 processor
- At least 16 GB RAM
- 512 Solid State Drive (SSD) with at least 200 GB of disk space free for installation of software
Necessary software will be provided free-of-charge to participants for the duration of the course.
Participants without the required hardware would need to face the consequences of not able to complete the labs and assignments required by the course.
Minimum Entry Requirements
Students enrolled in the Specialist Diploma in Data Science (Big Data and Streaming Analytics) must satisfy at least one of the following entry requirements:
(i) Any diploma from a polytechnic in Singapore and
• a C6 or better in Elementary Mathematics in the O-level examinations;
• or a pass in a one-semester polytechnic mathematics module;
• or relevant work experience (considered on a case-by-case basis).
(ii) Any degree from one of the following Singapore universities: NUS, NTU, SMU, SUTD, SIT, or SUSS.
Candidates with degrees from other universities will be considered on a case-by-case basis.
Due to intensive programming requirements of the course, applicants should have at least 1 year programming experience with any of the following programming languages:
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.
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. Each PDC comprises two modules and the details are as follows:
Please click here for Module Synopsis
PDC 1 Certificate in Fundamentals of Data Science
Module 1 - Introduction to Statistics for Data Science
Module 2 - Introduction to Programming for Data Science
PDC 2 Certificate in Big Data and Streaming Analytics
Module 1 – Big Data Platforms
Module 2 – Streaming Analytics
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.
Click here for Funding Incentives and Fees Matters.
|Specialist Diploma in Data Science (Big Data and Streaming 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||WORKFARE TRAINING SUPPORT SCHEME||OTHERS / REPEAT STUDENTS|
|Certificate in Fundamentals of Data Science||$421.79||$281.20||$1,124.78||$290.39||$158.99||$2,811.96|
|Certificate in Big Data and Streaming Analytics||$421.79||$281.20||$1,124.78||$290.39||$158.99||$2,811.96|
|Total Course Fees:||$843.58||$562.40||$2,249.56||$580.78||$317.98||$5,623.92|
Other Fees Payable:
|FEE DESCRIPTION||PER SEMESTER (AFTER GST)|
| ||SINGAPORE CITIZENS||SINGAPORE PR AND OTHERS|
|Statutory Licence Fee (CLASS)||$1.00||$1.00|
|Insurance Fee (GPA)||$1.70||$1.70|
- The fees shown (inclusive of 7% GST) are indicative as they are based on prevailing funding policies and subject to review.
- Post-Diploma Certificate Fee is payable on a semester basis.
- 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.
Date of Course Commencement:
14 Oct 2019
1 Jun 2019 - 31 Jul 2019
* Registration may be closed once seats are filled up
2 evenings a week
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 is compulsory. Please refer to the SP academic calendar.
240 hours (1 year)
For course specific details,
please contact the course manager:
Name: Dora Chua Heok Hoon