Master of Science in Data Science

(N-DL/0613/7/0015) (10/28) (MQA/PSA 16962)

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Introduction

One of the important approaches to achieve competitiveness in digital transformation is through a data-driven approach. With the right data science capabilities, the human capital development from the computing area is highly required in order to meet the calls for under-explored hydrocarbon reserve all over the world. This trend brings about many benefits to the nation and the people, but at the same time has introduced acute shortage of skilled manpower in this area. The requirements for knowledge workers with MSc and PhD qualifications have increased.​

Programme Objectives

Programme Outcomes

At the end of the program, graduates should be able to:

1. Integrate advanced knowledge related to current issues in Data Science.
2. Recommend innovative solutions that are at the forefront of developments in the field.
3. Evaluate data solutions and tools in terms of their usability, efficiency, and effectiveness.
4. Demonstrate effective interaction within a group and with diverse audiences through project discussions related to the fields of study.
5. Demonstrate effective communication by publishing and presenting technical materials in the fields of study.
6. Utilize digital skills to acquire, interpret, and extend knowledge in data science.
7. Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to the field of study.
8. Apply numerical skills to acquire, interpret, and extend knowledge in data science.
9. Exhibit capabilities to extend knowledge through lifelong learning in the field of study.
10. Exhibit capabilities to extend knowledge with an entrepreneurial mindset in the field of study.
11. Uphold professional and ethical practices in conducting research and delivering services related to the field of study.

What is ODL & How it is Conducted in UTP

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

In UTP, ODL is conducted as follows:

• 100% online with self-instructional materials (SIM)
• Live class sessions for courses taught
• Online open book final exams
• Classes held after working hours/over the weekend

Programme Highlights

 

Programme Details

Department: Computer & Information Science Department

Intakes: January, May, and September

Mode of Delivery: Fully online (Open Distance Learning)

Duration: 12 months – 36 months

Entry Requirements

• Bachelor’s Degree in Computing from a recognised university with a minimum CGPA of 2.75 or its equivalent.
• Bachelor’s Degree in Computing with a CGPA of 2.50-2.74 or its equivalent will require internal rigorous assessment.
• Bachelor’s Degree in Computing with a CGPA of 2.00-2.49 or its equivalent will require 5 years of working experience and internal rigorous assessment.

Other qualifications equivalent to a Bachelor’s degree (Level 6, MQF) in Computing or related fields recognised by the Government of Malaysia must undergo appropriate pre-requisite courses as determined by the HEP.

*Candidates without a qualification in the related fields or relevant working experience must undergo appropriate pre-requisite courses as determined by the HEP and meet a minimum CGPA of 2.00 with a minimum of five (5) years of working experience in related fields and rigorous internal assessment.

APEL A Field

Apply with your working experience. Candidates who satisfy APEL A requirements are eligible to enrol.

English Requirements

• A minimum TOEFL score of 550 or equivalent
• A minimum IELTS score of 6.0 or equivalent
• Native English speakers or those holding a degree with English as the medium of instruction may be exempted from this requirement.
  

Estimated Total Cost Fee

• RM (Malaysian) – RM23,550
• RM (International) – RM30,650

Career Prospects

Among the possible career prospects, but not limited to:

• Data Analyst
• Business Intelligence (BI) Analyst
• Data Scientist
• Machine Learning Engineer
• Data Engineer

These career prospects are relevant to many industries.

Programme Curriculum Structure and Programme Module Synopsis

Candidates are required to complete total of 40 credit hours. The programme's curriculum structure is as follows:

Category​​​	Module	Credit Hour
​​​Core​	Data Science Concept	3
	Data Management	3
	Data Analytical Programming	3
	Data Mining and Machine Learning	3
	Statistical Method for Data Analysis	3
Core Specialisation (Choose 1 Specialisation) ​	Advanced Data Analytics
	Digital Analytics	3
	Real-time Analytics	3
​	Data Engineering
	Numerical Optimisation	3
	Deep Learning	3
University Requirement	Big Data Analytics	3
	IT Project Management	3
National Requirement	Research Method in IT	3
Project	MSc Project 1	3
	MSc Project 2	7
TOTAL		40

As per requirement by Malaysian Qualification Agency (MQA), candidates coming from non-discipline into MSc in Data Science programme (such as engineering and business) have to take TWO pre-requisite courses before enrolling for the MSc programme. The two pre-requisite courses are (1) Software Engineering and (2) Object Oriented Programming.

Contact Information

Programme Manager: 

Ts. Dr. Emelia Akashah Patah Akhir

Email: emelia.akhir@utp.edu.my

Direct Line: +6053687476

Academic Executive: 

Ms. Fathiah Ruhana Zainonfetry

Direct Line: +6053687370

General Inquiries: 

​Ms. Nurul Asmira Sulaiman

Email: asmira.sulaiman@utp.edu.my

Direct Line: +6053688192​​

These career prospects are relevant to many industries.

FAQ