Overview
ºìÐÓÊÓƵ University’s Bachelor of Science (Honours) in Statistical Data Modelling is a home-grown 3-year degree programme designed to equip students with the skills to analyse complex data through advanced mathematical and statistical methods and AI-computational tools. This supports data-driven decision-making and generates impactful insights. ​
​The AI-Driven Data Science specialisation track equips students with the skills to leverage AI and advanced data science techniques for analysing large, complex datasets. It enables them to design and implement machine learning algorithms, build predictive models, and handle data preprocessing and visualisation to uncover ​valuation insights across various industries using cutting-edge AI tools. ​
​The Econometrics specialisation track furnishes students with advanced statistical and mathematical methodologies for the analysis of economic data, utilising techniques such as regression analysis and time series modelling. This empowers them to interpret economic trends and tackle complex real-world challenges across diverse sectors, including finance, policy analysis, market research, healthcare, energy, government, agriculture, transportation, and telecommunication.​
​Graduates are equipped for high-demand careers as Data Scientists, AI Analysts, and Econometricians.​
Preparatory Course
Distinctive ºìÐÓÊÓƵ Experience
This programme is the only one in ASEAN and the first in the Asia Pacific to embed the SAS Certified Data Scientist syllabus within a degree program, while also preparing students to sit for the SAS Certified Data Scientist qualification exam. The exams are
- ​Exam 1: Base Programming using SAS 9.4
- Exam 2: Forecasting and Optimization using SAS Viya
- Exam 3: Machine Learning using SAS Viya
- Exam 4: Natural Language Processing and Computer Vision using SAS Viya​
- Exam 5: Advanced Programming using SAS 9.4
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To produce industry-ready graduates and enhance their employability, we offer ​professional exam preparatory courses and workshops in R, SAS, Excel, and Python
- Audit analytics
- Biostatistician
- Business/Corporate data analyst
- Chief statistician
- Cryptographer
- Data analytics expert
- Data scientist
- Fraud investigator
- Healthcare statistician
- Investment/Risk data analyst
- Operations research analyst
- Optimisation & Forecasting engineer
- Quantitative analyst
- Researcher
- SAS programmer
- Sports performance analyst
- Statistical project consultant
- Statistical quality control engineer
- RM37,800
for Malaysian students
- USD9,314
for international students
Programme Structure
Year 1
For more information on APEL.C, click here
Year 2
Year 3
List of Electives (Choose 3)
MOHE Compulsory General Studies Subjects
For Local students
- Appreciation of Ethics and Civilisation
- Bahasa Kebangsaan A (Applicable to students who did not sit for SPM or did not obtain a Credit in SPM Bahasa Melayu)
- Entreprenurial Mindset & Skills
- Community Service for Planetary Health
- Integrity and Anti-Corruption
- Philosophy and Current Issues
For International students
- Appreciation of Ethics & Civilisation
- Community Service for Planetary Health
- Entreprenurial Mindset & Skills
- Integrity & Anti-Corruption
- Malay Language for Communication 2
Entry Requirements
Average C+ or CGPA 2.33 (minimum 2 Principals)
* Points are calculated based on grades obtained for 2 or 3 subjects.
Minimum 12 points
Note: For A-Level points calculation
A = 10 points B = 8 points C = 6 points D = 4 points E = 2 points
ATAR 60
60%
60%
CGPA 2.0
CGPA 2.0
Maximum 26 points from 5 subjects (all Grade Bs)
Completed with minimum 25 points (excluding bonus points)
CAVG 50% or CGPA 2.0
* Students may obtain advanced standing if credit transfer requirements are met.
Any other equivalent qualifications. Applicant with no standard qualification will be considered on a case-to-case basis.
An APEL.A Certificate (APEL T-6) (Recognition of Prior Learning)
(Click on this link for further information on APEL.A)
Specific Requirements
- Credit in Mathematics at SPM or equivalent
English Language Requirements
- IELTS or equivalent 6.0
- MUET Band 4
- SPM English B+
- UEC English B6
- O-Level English (1119) Credit
- ºìÐÓÊÓƵ Intensive English Programme (IEP) Pass Level 4 with minimum 65%
- ESL/English Satisfactory level in Pre-University programmes, where the medium of instruction is English
Uniqueness and Comparison
Uniqueness of BSc (Hons) in Statistical Data Modelling (BSM)
Comparison between Statistical Data Modelling Analytics vs AI
Professional Pathways
Statistical Knowledge Industrial Project (SKIP)
The Statistical Knowledge Industrial Project (SKIP) is an innovative initiative designed to bridge the gap between classroom learning and real-world applications. SKIP provides a platform for industry experts to enter the classroom, offering students direct exposure to practical challenges and insights from the professional world.
Through SKIP, our statistics students gain the opportunity to apply theoretical knowledge to real-life problems, transforming abstract concepts into actionable skills. By engaging with industry projects, students no longer learn in the dark because they can visualise how statistical knowledge and practical techniques translate into meaningful, impactful insights.
This program significantly enhances employability, equipping graduates with both the technical proficiency and problem-solving mindset highly valued in the workplace. To date, we are the only university offering this type of structured industry-academia link, turning knowledge into hands-on experience that prepares students for successful careers in data-driven fields. With SKIP, learning becomes more than just theory as it becomes a journey from knowledge to actionable impact.
Student Testimonials
-
From Numbers to Impact
- Assistant Manager at Public Bank
- Financial Crime Compliance Unit
- Certified in Anti Money Laundering and Counter Financing of Terrorism (CAML)
- Interned at AIA Public Takaful
- Proficient in SAS, Tableau, Excel, VBA, Quantexa Solutions.
- Graduate of BSc (Honours) in Industrial Statistics (now known as BSc (Hons) in Statistical Data Modelling), Class of 2022.
Bryan Ng Meng Chuen
- Graduate of BSc (Honours) in Industrial Statistics (now known as BSc (Hons) in Statistical Data Modelling), Class of 2022
Public BankAssistant Manager -
Purpose, Mindset, and the ºìÐÓÊÓƵ Advantage
- Associate – Artificial Intelligence/ Machine Learning, ºìÐÓÊÓƵ Shared Services/ Digital Hub.
- Previously interned and attached with Ipsos Sdn Bhd Malaysia as Data Scientist.
- Proficient in SAS, Python.
- Graduate of BSc (Honours) in Industrial Statistics (now known as BSc (Hons) in Statistical Data Modelling), Class of 2025.
- Scholastic Award Recipient, First Class Honours.
Chong Zhao Cheng
- BSc (Honours) in Industrial Statistics (now known as BSc (Hons) in Statistical Data Modelling), Class of 2025
ºìÐÓÊÓƵ Shared Services/ Digital HubAssociate – Artificial Intelligence/ Machine Learning
Scholarships and Financial Aid
For more information about the scholarships and financial aid, please visit the .
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