Bachelor of Science (Honours) in Statistical Data Modelling

Overview

ºìÐÓÊÓÆµ 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

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sas

 

Distinctive ºìÐÓÊÓÆµ Experience

This programme equips students with AI-driven decision-making skills through ​computational tools, while also preparing them to successfully obtain the SAS Certified ​Data Scientist qualification.​

  • ​Exam 1: Data Curation for SAS Data Scientists​
  • Exam 2: Predictive Modelling​
  • Exam 3: Advanced Predictive Modelling​
  • Exam 4: Text Analytics, Time Series, Experimentation and Optimisation​

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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

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SAS Academic Badge

 

Intakes
February, April, September
Duration
3 Years (full-time)
Career Prospects
  • 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
Estimated Annual Course Fee
  • RM35,800
    for Malaysian students
  • USD8,456
    for international students
International students must pay their fees in RM equivalent. The USD here is just an indicative/estimation and subject to the prevalent exchange rate

Programme Structure

Year 1

For more information on APEL.C, click here

Advanced Calculus
AI Foundation and Applications
Calculus
Data Modelling Essentials
Introduction to Operations Research
Introduction to Probability
Principles of Economics
Linear Algebra & Applications
Principles of Business Finance
Programming Principles

Year 2

AI-Driven Forecasting and Modelling
Computer-Intensive Statistical Methods
Design of Experiments
Essentials of Employability
Free Elective 1
Introductory Econometrics
Mathematical Statistics I
Quality Control and Survey Sampling
Statistical Data Technologies and Fluency

Year 3

Applied Econometrics
Internship
Free Elective 2
Machine Learning Techniques for Data Mining
Multivariate Analysis
Time Series & Forecasting

List of Electives (Choose 3)

Advanced Data Analytics
Applied Nonparametric Statistics
Applied Time Series Econometrics
Discrete Mathematics
Research Project
Risk Theory
Stochastic Processes
Simulations and Credibility Theory
Survival Models

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
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Student with lecturer

Entry Requirements

STPM

Average C+ or CGPA 2.33 (minimum 2 Principals)

A-Level*

* 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

Australian Matriculation

ATAR 60

Canadian Matriculation

60%

Monash University Foundation Year

60%

ºìÐÓÊÓÆµ Foundation in Arts

CGPA 2.0

ºìÐÓÊÓÆµ Foundation in Science Technology

CGPA 2.0

Unified Examination Certificate

Maximum 26 points from 5 subjects (all Grade Bs)

International Baccalaureate

Completed with minimum 25 points (excluding bonus points)

ºìÐÓÊÓÆµ Diploma*

CAVG 50% or CGPA 2.0
* Students may obtain advanced standing if credit transfer requirements are met.

Other Qualifications

Any other equivalent qualifications. Applicant with no standard qualification will be considered on a case-to-case basis.

APEL.A

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 B4
  • O-Level English (1119) Credit
  • ºìÐÓÊÓÆµ 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

Scholarships and Financial Aid

For more information about the scholarships and financial aid, please visit the .

ºìÐÓÊÓÆµ Campus

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Monday to Friday: 9am - 5:30pm MYT

Call +6 (03) 7491 8622