Modelling Fundamentals & Statistical Learning
About This Course
This is a module under the Specialist Diploma in Data Science (Predictive Analytics).
What You'll Learn
Alongside these foundations, students will explore how generative AI can be used as a responsible analytical co-pilot to support tasks such as exploratory analysis, code scaffolding, and interpretation of model outputs. Emphasis is placed on understanding where GenAI can enhance efficiency and insight, and where human reasoning, statistical assumptions, and validation remain critical. By the end of the module, students will be equipped with the fundamentals needed to understand and perform effective data analysis and build predictive models using statistical methods and machine learning techniques, while critically evaluating and validating any GenAI-assisted outputs.
Entry Requirements
Applicant must satisfy at least one of the following entry requirements:
(i) An Engineering/ IT diploma or degree from a recognised polytechnic* or university** in Singapore
(ii) Any other diploma or degree from a recognised polytechnic* or university** in Singapore and possess a Pass grade in either GCE ‘O’ level Mathematics or a Mathematics subject at diploma level.
* NYP, NP, RP, SP, or TP
** NTU, NUS, SIT, SMU, SUSS, or SUTD (candidates with degrees from other uni are considered on a case-by-case basis)
(iii) Any other tracks of Specialist Diploma in Data Science offered by Singapore Polytechnic (candidates may exempt PDC1 modules and directly enrol for PDC2 modules)
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.