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Data Scientist.webpMaster of Science in Predictive Analytics

(N-DL/0588/7/0002) (MQA/PSA18316)​


Introduction

The Fundamental and Applied Sciences​ ​Department (FASD), Universiti Teknologi PETRONAS, is offering the Master of Science (MSc) in Predictive Analytics to address the increasing demand for data-driven decision-making across various industries. This programme equips graduates with advanced analytical and computational skills to extract valuable insights from complex data, supporting informed decision-making in business, engineering and other domains. 

The MSc in Predictive Analytics aims to bridge the gap between theoretical knowledge and industry applications, preparing graduates to become specialists in data analytics, machine learning, and artificial intelligence. With a strong emphasis on real-world problem-solving, the programme integrates modelling, decision making ​techniques, and domain-specific applications to support Malaysia’s digital transformation agenda and global industry needs. 

This programme is designed for professionals and graduates seeking to enhance their expertise in predictive modelling, big data analytics, and decision intelligence, contributing to the advancement of data science and analytics-driven innovations.

Programme Objectives

1. Predictive Analytics specialists with insights to articulate industry problems and provide solutions.
2. Predictive Analytics specialists with the potential to become leaders equipped with relevant skills for continuous improvement in industrial processes and performances.

Programme Outcomes

Upon the completion of this programme, the graduates should be able to:
1. Demonstrate analytical and critical evaluation of complex information using predictive analytics techniques. 
2. Apply predictive analytics knowledge and techniques to resolve complex problems. 
3. Conduct standard practical skills and investigative techniques for problems that required predictive analytics knowledge. 
4. Communicate and critique knowledge and idea using appropriate techniques to peers, experts, and non-experts.  
5. Competently use digital technologies to address the implementation of predictive analytics techniques. 
6. Demonstrate autonomy, independence, and leadership in the context of complex application. 
7. Exemplify self-advancement through continuous academic or professional development. 
8. Demonstrate ability to make decision on complex issues based on critical reflections and ethical considerations. ​​

What is ODL & How it is Conducted in UTP

ODL stands for Open and Distance Learning, a way of study remotely that offers flexibility for learning from anywhere, anytime and anyhow with self-directed learning strategies

In UTP ODL is conducted as below:
100% online with self-instructional materials (SIM)
Live class session for courses taught
Classes after working hours/over the weekend
Online open book final exam


Programme Highlights

​Core Specialisation:
1. Business Analytics

Business Intelligence

Behavioural Analytics

2. Predictive Maintenance

Maintenance Analytics

Performance Evaluation


Adjunct Lectures: 
1. PETRONAS
2. Department of Statistics Malaysia (DOSM)
3. Bursa Malaysia

Programme Details

​Department: Fundamental and Applied Sciences

Intakes: January, May, and September

Mode of Study: Open & Distance Learning (ODL)

Course Duration: 12 – 36 months

Entry Requirements
1. Candidates must hold a bachelor’s degree (in engineering, science and technology discipline) with minimum CGPA 2.50/4.00, or equivalent qualifications from a recognized university OR 
Candidates with bachelor’s degree (other than above disciplines) with minimum CGPA 2.50/4.00, or equivalent qualifications from a recognized university, can be admitted and must pass UTP internal assessment. 
2. Candidates with bachelor’s degree with minimum CGPA 2.00 but below 2.50, can be admitted and must have five (5) years working experience and pass UTP internal rigorous assessment. 


English Requirements

1. A minimum TOEFL score of 550 or equivalent. 
2. A minimum IELTS score of 6.0 or equivalent. 
3. Native English speakers or holding a degree with English as the medium of instruction may be exempted from requirement (1) and (2).


Pre-requisite courses
Applicant with a Bachelor's Degree in disciplines other than engineering, science, or technology must complete the following pre-requisite courses:
1. Statistics and Applications 
2. Structured Programming
These courses will be conducted 100% online.

Estimated Total Cost Fee

Local: RM 23,900
International: RM 34,900

Career Prospects
Predictive Modeler, Business Intelligence Specialist, Researcher, Entrepreneur and Academic

Programme Curriculum Structure and Programme Module Synopsis

The MSc in Predictive Analytics is structured to span three trimesters (one year), accumulating a total of 40 credit hours.

 

Semester Cl​​assification Course Credit Value
1​​​​

National Requirement

Core Discipline

Core Discipline

Core Discipline

Research Methodology

Statistical Analysis

Decision Making Techniques

Programming and Data Visualisation

2

4

4

4

2

University Requirement

Core Discipline

Core Specialisation

Industrial Project

Project Management

Data Mining and Machine Learning

Specialisation 1

Industrial Project 1

2

4

3

3

3

Core Discipline

Core Specialisation

Industrial Project

Forecasting Techniques

Specialisation 1

Industrial Project 2

4

7

3

 


Core Specialisations Courses: Choose any of the following sets A or B for core specialisation

A: Business Analytics
Course Credit Value

Business Intelligence

Be​havioural Analytics

3

3

 

B: Predictive Maintenance
Course Credit Va​lue

Maintenance Analytics

​Performance Evaluation

3

3​



Contact

Programme Manager
Ts. Dr. Mohana Sundaram Muthuvalu
Email: mohana.muthuvalu@utp.edu.my
Direct Line: +6053687695

Academic Executive
Ms Nursuraya M Zulkifli Manisegaran
Email: nursuraya.mzulkifli@utp.edu.my
Direct Line: +6053687681

General Inquiries
Ms Nurul Asmira Sulaiman
Email: asmira.sulaiman@utp.edu.my
Direct Line: +6053688192​​​​​