Master in Data Science
Source: https://www.utp.edu.my/Pages/Admission/Postgraduate/Master-by-Coursework/Master-in-Data-Science-(ODL).aspx Parent: https://www.utp.edu.my/Pages/Students/Prospective%20Files/Programme-Offered.aspx
Master by Coursework
- MBA in Energy Management
- MSc in Asset Management and Maintenance
- MSc in Applied Computing
- MSc in Corrosion Engineering
- MSc in Drilling Engineering
- MSc in Electronic System Engineering
- MSc in Industrial Environmental Engineering
- MSc in Offshore Engineering
- MSc in Petroleum Engineering
- MSc in Petroleum Geoscience
- MSc in Process Integration
- MSc in Process Safety
Master by Coursework (ODL)
- MBA in Energy Management (ODL)
- MSc in Asset Management and Maintenance (ODL)
- MSc in Electronic Systems Engineering (ODL)
- MSc in Offshore Engineering (ODL)
- MSc in Geoscience (ODL)
- MSc in Process Integration (ODL)
- MSc in Process Safety (ODL)
- MSc in Drilling Engineering (ODL)
- MSc in Applied Computing (ODL)
- MSc in Industrial Environmental Engineering (ODL)
- MSc in Corrosion Engineering (ODL)
- MSc in Petroleum Engineering (ODL)
- MSc in Data Science (ODL)
- MSc in Predictive Analytics
Master 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
- Data Scientist with advanced knowledge in Data Science, capable of adopting best methodologies and techniques to provide innovative solutions to various industries and society.
- Data Scientist with leadership skills and the ability to communicate and interact effectively with diverse stakeholders.
- Data Scientist with positive attitudes, engaging in lifelong learning activities, and entrepreneurial mindset for continual career development.
- Data Scientist who upholds and practices ethics and professionalism for self and profession integrity.
Programme Outcomes
At the end of the programme, graduates should be able to:
- Integrate advanced knowledge related to current issues in Data Science.
- Recommend innovative solutions that are at the forefront of developments in the field.
- Evaluate data solutions and tools in terms of their usability, efficiency, and effectiveness.
- Demonstrate effective interaction within a group and with diverse audiences through project discussions related to the fields of study.
- Demonstrate effective communication by publishing and presenting technical materials in the fields of study.
- Utilize digital skills to acquire, interpret, and extend knowledge in data science.
- Demonstrate leadership, teamwork, autonomy, and responsibility in delivering services related to the field of study.
- Apply numerical skills to acquire, interpret, and extend knowledge in data science.
- Exhibit capabilities to extend knowledge through lifelong learning in the field of study.
- Exhibit capabilities to extend knowledge with an entrepreneurial mindset in the field of study.
- 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 session for courses taught
- Online open book final exams
- Classes held after working hours/over the weekend
Programme Highlights
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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.\
Pre-requsite\
- Object-Oriented Programming
- Software Engineering
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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 |
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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.
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Contact Information
Programme Manager:
Ts. Dr. Emelia Akashah Patah Akhir
Email: emelia.akhir@utp.edu.my
Direct Line: +6053687476
General Inquiries:
Ms. Nurul Asmira Sulaiman
Email: asmira.sulaiman@utp.edu.my
Direct Line: +6053688192\
These career prospects are relevant to many industries.
FAQ
Q: I don’t have basic programming background. Can I still pursue this programme?
A: Yes, definitely. For those coming from non-computing background, you need to take prerequisite courses to prep you with basic programming skill.
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Q: I work in a non-computing industry. Is this programme relevant to me?
A: Graduates with an MSc in Data Science are highly sought after in a variety of industries, as they possess skills in data analysis, machine learning, programming, and statistical modeling. The demand for data professionals continues to grow, opening a wide range of career prospects.
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Q: What are the skillset I will obtain from this programme?
A: An MSc in Data Science equips you with skills in programming (Python, R, SQL), data analysis, big data tools (Hadoop, Spark), database management, and cloud computing (AWS, Azure). You’ll gain expertise in statistical analysis, machine learning, AI (including deep learning, NLP, and computer vision), and data visualization (Tableau, Power BI). The program also develops critical thinking, problem-solving, and communication skills for presenting data insights, along with knowledge of data ethics, privacy laws etc.