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EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
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EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

(43) Google reviews

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Msc in Data Science and Business Analytics

Course overview

Statistics
Qualification Master's Degree
Qualification Subtype Master of Science (MSc)
Coursework / Research Coursework
Study mode Full-time, Part-time
Duration 1 year
Intakes January, April, May, June, August, October, December
Tuition (Local students) S$ 12,316
Tuition (Foreign students) S$ 13,524

Subjects

  • Business

  • Information Tech (IT)

About

APU's MSc in Data Science and Business Analytics provides students with advanced technologies aligned with Industry 4.0, along with the opportunity to earn a Joint Professional Certification from SAS Institute, USA. The curriculum includes hands-on learning through mini projects, covering topics such as Analytical Technologies, R & SAS Modelers, Data Visualization, Behavioral Studies, Forecasting, and Business Intelligence. The program benefits from annual reviews by international university partners and an Industry Advisory Panel of data experts. Students also have access to research opportunities through APU’s Centre of Analytics (APCA).

This program, available full time (1+ years) and part time (2.5-3 years), is designed to offer:

  • Knowledge and practical skills in data science, big data analytics, and business intelligence.
  • A comprehensive understanding of the impact of data science on modern processes and business.
  • Exposure to data science tools, techniques, and methods for collecting and utilizing data to transform it into valuable insights.

 

Admissions

Intakes

Fees

Tuition

S$ 12,316
Local students
S$ 13,524
Foreign students

Estimated cost as reported by the Institution.

Application

S$ 241
Local students
Data not available
Foreign students

Student Visa

S$ 799
Foreign students

Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.

Entry Requirements

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

INTERNATIONAL STUDENTS

• IELTS : 6.0

 

Curriculum

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: 1 Month (Full time) / 4 Months (Part time)

  1. Introduction to R-programming
  2. Statistics
  3. Database for Data Science
  4. Programming in Python

Core Modules

  1. Big Data Analytics & Technologies
  2. Data Management
  3. Business Intelligence Systems
  4. Research Methodology for Capstone Project
  5. Applied Machine Learning
  6. Data Analytical Programming
  7. Multivariate Methods for Data Analysis
  8. Advanced Business Analytics and Visualisation
  9. Capstone Project 1
  10. Capstone Project 2

Specialisation Modules (Choose any 1 Pathway)

Pathway 1 (Business Intelligence):

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

Pathway 2 (Data Engineering):

  1. Cloud Infrastructure and Services
  2. Deep Learning
  3. Natural Language Processing OR Building IoT Applications OR Data Protection and Management