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
2. Predictive Maintenance
Adjunct Lectures:
1. PETRONAS
2. Department of Statistics Malaysia (DOSM)
3. Bursa Malaysia
Programme Details
Department: Department of 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 |
Classification |
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
7
|
3
|
Core Discipline
Core Specialisation
Industrial Project
|
Forecasting Techniques
Specialisation 1
Industrial Project 2
|
4
3
7
|
Core Specialisations Courses: Choose any of the following sets A or B for core specialisation
|
A: Business Analytics |
|
|
Course |
Credit Value |
|
Business Intelligence
Behavioural Analytics
|
3
3
|
|
B: Predictive Maintenance |
|
|
Course |
Credit Value |
|
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
