PhD in Data Science

Programme Learning Outcomes (PLO)                          

PLO 1                   
Formulate comprehensive, systematic, integrated, new, complex and abstract ideas of current critical issues in the advanced frontiers of knowledge in the latest focus areas of Data Science.

PLO 2                   
Elaborate new, complex, abstract ideas and current critical issues in the most advanced frontiers of knowledge in the latest focus areas of Data Science and other related areas, and modify existing concepts and practices.

PLO 3                   
Build mastery of practical, technical skills/practices and scientific skills at the forefront of one or more areas of specialisation and develop new complex skills, techniques and solutions to solve new, highly complex and emerging problems.

PLO 4                   
Create effective collaboration with different people in learning and working communities and other groups and networks, ethically and professionally.

PLO 5                   
Compile information, insights, ideas and problems, and propose solutions cogently/coherently to peers, scholarly community and society in the latest focus areas of Data Science.

PLO 6                   
Develop new appropriate tools/methodologies to support and enhance research in the latest focus areas of Data Science.

PLO 7                   
Critically formulate numerical and scientific data using quantitative or qualitative problem-solving tools.

PLO 8                   
Construct substantial autonomy, independence, leadership, and professionalism in research management to contribute to the technological, social and cultural progress of academic and professional practice to the society at large on emerging issues at professional levels.

PLO 9                   
Improve responsibility to integrate knowledge for lifelong learning with developing new ideas, solutions and systems, and overall management of one’s research organisation.

PLO 10                   
Invent entrepreneurial ventures and projects in the latest focus areas of Data Science.

PLO 11                   
Discuss emerging ethical, legal and professional issues, their complexities and implications for advancing research in the fields and professionally maximise contribution to social, technological and economic developments.

First semester:

List of Compulsory Courses

• TDS5908 Research Methodology
• TDS5101 Advanced Data Science
• TDS5901 Research Seminar

TDS6999 Doctoral Research (Stage-1)

• Research proposal writing

Second semester:

Choose one elective course     

• TDS5201 Programming for Data Science
• TDS5301 Big Data Analytics
• TDS5401 Advanced Data Engineering

TDS6999 Doctoral Research (Stage-2) Completing research proposal

• Proposal defend should be approved maximum in one year.

Third – Sixth semester:

1. TDS6999 Doctoral Research (3-6)
2. Viva-Voce of thesis defense examined by internal and external examiners.
3. Prior to Viva Voce, at least two publications in SCOPUS-indexed journal or conference proceedings.

Programme Duration (Full Time)

• 3 years (6 semesters)

   

Entry Requirements

1. A Master’s degree (Level 7, MQF) in Computing or related fields as accepted by the Senate; OR
2. A Master’s degree (Level 7, MQF) in non-Computing fields with a minimum of five (5) years of working experience in Computing or related fields must undergo appropriate prerequisite courses as determined by HEP; OR
3.  A Master’s degree (Level 7, MQF) in non-Computing fields with less than five (5) years of working experience in Computing or related fields must undergo rigorous internal assessment as determined by HEP to identify the appropriate prerequisite courses that equivalent to their working experience in the Computing or related fields; OR
4. Other qualifications equivalent to a Master’s degree (Level 7, MQF) recognised by the Malaysian Government.

English Requirement

English Competency Requirement for International Student:

• Test of English as a Foreign Language (TOEFL) score of 500, or 
• International English Language Testing System score of 5.0 or its equivalent, or
• Achieve a minimum Band 4 in Malaysian University English Test (MUET), or 
• Any equivalent to Common European Framework of Reference for Languages, CEFR (B2).

MYR 3,625/ Semester                       
(Local Students)

MYR 5,125/ Semester                       
(International Students)

Excluding immigration fees, insurance and dormitory.

Note: 

1. Student pass fees for international students are subjected to a determination under the Malaysian Immigration Department.
2. Student insurance fees are subjected to the statutory provisions of the University and local authorities.
3. Student accommodation fees are determined by university rules and are available upon request.

Muhammad Akmal Remli 

Senior Lecturer (Visiting)

Areas of Expertise 

Artificial Intelligence, Deep Learning, Machine Learning, Computational Systems Biology.

Education 

Ph.D., Computer Science, 2018, Universiti Teknologi Malaysia (UTM), Malaysia.

Master, Computer Science, 2014, Universiti Teknologi Malaysia (UTM), Malaysia.

Bachelor, Computer Science, 2006, Universiti Teknologi Malaysia (UTM), Malaysia.

If you do not have title for your research, you may consider these topics

Hadhrami Ab Ghani

Senior Lecturer (Visiting)

Areas of Expertise 

Intersection of cutting-edge communications, artificial neural networks, network security, computer vision, and data science. I delve into these domains to explore and innovate, bridging the gaps between technology and theory.

Education 

Ph.D., Electrical Communication, 2011, Imperial College London, United Kingdom.

Diploma, Communication and Signal Processing, 2007, Imperial College London, United Kingdom.

Master, Telecommunication Engineering, 2005, University of Melbourne, Australia.

Bachelor, Computer Science, 2002, Multi Media University (MMU), Malaysia.

If you do not have title for your research, you may consider these topics