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MSc in Data Science and Business Analytics

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APU University Malaysia

MSc in Data Science and Business Analytics

university icon
APU University Malaysia

MSc in Data Science and Business Analytics

Qualification
Master's Degree
Duration
1 years
Intake
JunJunSepSep
English Requirement
IELTS 6.0
Offer Letter
Free
Class Type
Physical
Course Fee for International Students
Yearly Tuition fees
Year Fee
1st YearMYR 44,800
Other Fees
Description Fee
Library & Personal Bond Deposit (Refundable)MYR 1,500
University Administrative FeesMYR 2,550
Visa and InsuranceMYR 5,800

Would you like to apply to
APU University Malaysia ?

Embark on a transformative journey with APU University Malaysia MSc in Data Science and Business Analytics program. Explore a myriad of invaluable insights and skills, detailed below:

What you will learn in a glance?

Upon completing the MSc in Data Science and Business Analytics, graduates will possess a diverse skill set tailored for success in today's data-driven business landscape. They'll adeptly collect, clean, and analyze large datasets to extract valuable insights, driving strategic decision-making. Additionally, graduates excel in predictive modeling, fostering innovation, and effectively communicate findings to stakeholders. Ethical considerations and regulatory compliance are also emphasized, ensuring responsible data handling. Overall, graduates emerge as versatile professionals capable of driving organizational growth and innovation through strategic data analytics.

Dual Degrees from APU and DMU United Kindom

Students who joined the MSc in Data Science and Business Analytics program at APU University Malaysia will have the option to apply for the APU-DMU Dual Degree Scheme. Under this Scheme, students will be able to get 2 Degree Certificates and transcripts upon graduation: 1 from Asia Pacific University (APU), Malaysia, and 1 from De Montfort University (DMU), UK. please note this is optional and costs GBP 375 Per year. For more information about this Scheme (Click here)

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.

The programme comprises 4 pre-requisite modules (for non-Computing students), 11 coursework modules and a Capstone Project (2 parts).

PRE-REQUISITE MODULES
(FOR NON-COMPUTING STUDENTS: TO BE COMPLETED UPON 1st MONTH OF THE PROGRAMME)

  • 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
  • Capstone Project 1
  • Advanced Business Analytics and Visualisation
  • Capstone Project 2

SPECIALIZATION MODULES (CHOOSE 1 PATHWAY ONLY)

Pathway 1 (Business Intelligence):

  • Behavioural Science, Social Media and Marketing Analytics
  • Time Series 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
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