MSc in Data Science and Business Analytics (ODL)

This programme is specifically designed to provide:

• Knowledge and applied skills in data science, big data analytics, and business intelligence.
• An overall understanding of the impact of data science on modern processes and businesses.
• Exposure to data science tools and techniques, as well as methods of data collection and utilisation.
• The ability to turn data into useful information through various processes.

The Benefits of the Programme

• In addition to the degree award, a Joint Professional Certification will be offered by SAS Institute, USA.
• 30% of the curriculum includes mini projects assessed as in-course work, allowing for practical skills development in Data Analytics.
• The curriculum covers a wide range of subject matter, including:
  • Analytical Technologies
  • Exposure to tools such as R & SAS Modelers
  • Data Visualisation
  • Customer/User Behavioural Studies
  • Forecasting Methods
  • Presenting Business Intelligence reports
• External Programme Annual Reviews by International University Partners.
• Programme Support by an Industry Advisory Panel, including experts from:
  • Petronas ICT
  • RedTone
  • SharePoint
  • CyberSecurity Malaysia
  • Maxis
  • IBM
  • Microsoft
  • Fusionex
  • Axiata
• Research opportunities via APU’s Centre of Analytics (APCA).

Who Should Attend?

This programme is designed for students who:

• Want to gain knowledge and applied skills in data science, big data analytics, and business intelligence.
• Aim to develop analytical and investigative knowledge and skills using data science tools and techniques.
• Wish to enhance their critical interpretation skills and understanding of data science’s impact on modern businesses.
• Seek to identify and implement specific tools, practices, and techniques to improve data analysis.

General Requirements

• Bachelor’s degree in Computing or related fields with a minimum CGPA of 2.50, or its equivalent qualification as accepted by the Senate.
• Bachelor’s degree in Computing or related fields with a minimum CGPA of 2.00 and not meeting a CGPA of 2.50 can be accepted, subject to a rigorous internal assessment.
• Bachelor’s degree in non-related fields with a minimum CGPA of 2.00 as accepted by the Senate and with relevant working experience, subject to a rigorous internal assessment.
• Bachelor’s degree in non-related fields with a minimum CGPA of 2.00 as accepted by the Senate and without relevant working experience, subject to passing pre-requisite courses.

Δ Fundamental skills in programming, database, mathematics and statistics would be an added advantage.
* Applicants without a Computing-related Bachelor’s degree must pass the pre-requisite modules to continue with the Master’s Degree.

Note: The above entry requirements may differ for specific programmes based on the latest programme standards published by Malaysian Qualifications Agency (MQA).

English Requirements

• IELTS: 6.0

This programme comprises 11 coursework modules, including 8 core modules and 3 specialisation modules, and a Capstone Project (2 parts).

Pre-Requisite Modules (FOR NON-COMPUTING STUDENTS)

Duration: 4 Months 

• Introduction to R-programming
• Statistics
• Database for Data Science
• Programming in Python

Core Modules

• Big Data Analytics & Technologies
• Data Management
• Business Intelligence Systems
• Research Methodology for Capstone Project
• Applied Machine Learning
• Data Analytical Programming
• Multivariate Methods for Data Analysis
• Advanced Business Analytics and Visualisation
• Capstone Project 1
• Capstone Project 2

Specialisation Modules (Choose any 1 Pathway)

Pathway 1 (Business Intelligence):

• Behavioural Science, Social Media and Marketing Analytics
• Time Series Analysis and Forecasting
• Strategies in Emerging Markets OR Multilevel Data Analysis OR Operational Research and Optimization

Pathway 2 (Data Engineering):

• Cloud Infrastructure and Services
• Deep Learning
• Natural Language Processing OR Building IoT Applications OR Data Protection and Management