Certificate in Predictive Analytics

Training Provider: SINGAPORE POLYTECHNIC
Course Reference: TGS-2021006233
S$3,648

About This Course

The objective of the NSDPA programme is to

• build foundational skills and working knowledge in applied statistics and programming necessary for building broad knowledge in data science;
• develop deeper, specialised skillets in the area of statistical data analysis, modelling, prediction, forecasting and risk quantification;
• establish an understanding of practical applications of predictive analytics in industry.

What You'll Learn

Specialist Diploma in Data Science (Predictive Analytics), (NSDPA), is a program that spans over one academic year which seeks to build foundational statistical and programming skills for data science. Based on this foundational skillset, students will acquire specific, deeper statistical data analysis and modelling knowledge that are central to job roles of Data Analysts / Associate Data Engineer.

Entry Requirements

Polytechnic Diploma/ University with Engineering or IT diploma/degree:
Applicants must have an Engineering/ IT diploma or degree from a recognized polytechnic*/ university** in Singapore

Polytechnic Diploma/ University with Maths requirement:
Applicants must have any other diploma or degree from a recognized polytechnic*/ university** in Singapore, and possess a Pass grade in either GCE ‘O’ level Mathematics or a Mathematics subject at diploma level.

Recognition of Prior Learning (RPL):
Applicants with relevant work experience in a data-related or analytical role will be considered on case-by-case basis, with consideration of supporting evidence of competency readiness. Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. The Polytechnic reserves the right to shortlist and admit applicants.

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

Course Details

Duration 120 hours
Language English
Training Commitment Part Time
Total Enrolled 59 students
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Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.

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