Master of Computer Science (Research)

i. A Bachelor’s degree (MQF, Level 6) in computing or related fields with a minimum CGPA of 3.00 or equivalent, as accepted by Perdana University’s Senate;

OR

ii. A Bachelor’s degree (MQF, Level 6) in computing or related fields or equivalent with a minimum CGPA of 2.75 can be accepted subject to rigorous internal assessment;

OR

iii. A Bachelor’s degree (MQF, Level 6) in computing or related fields or equivalent with a minimum CGPA of 2.50 can be accepted subject to a minimum of FIVE (5) years of working experience in the related fields and rigorous internal assessment;

OR

iv. Candidate without a qualification in the related fields or relevant working experience must undergo appropriate prerequisite courses as determined by Perdana University and meet a minimum CGPA of 2.50 with minimum of FIVE (5) years of working experience in related fields and rigorous internal assessment;

OR

v. Other qualifications equivalent to a Bachelor’s degree (MQF, Level 6) in the field of computing or related fields recognized by the Government of Malaysia must undergo appropriate prerequisite courses as determined by Perdana University’s Senate.

International Students: Achieve a minimum score of 6.0 in the International English Language Testing System (IELTS) or equivalent.

If a student does not meet this requirement, Perdana University provides English proficiency courses to ensure that the student's proficiency is sufficient to meet the needs of the programme.

All students must register and pass the modules below:

CORE MODULES (Mandatory)

• Research Methods for Computer Science
• Quantitative Analysis

RESEARCH AREAS

• Artificial Intelligence (AI)
• Computer-Human Interface (HCI)
• Software Engineering
• Data Science and Analytics
• Computer Networks and Security
• Distributed Systems and Cloud Computing
• Algorithms and Optimization
• Computational Biology
• Graphics and Computer Vision
• Natural Language Processing (NLP)
• Machine Learning
• Bioinformatics

In-Depth Knowledge
Students develop a comprehensive understanding of their chosen research area, contributing new knowledge or innovations to the field.

Career Advancement
The programme prepares graduates for advanced roles in academia, industry leaders, and top-tier research institutions.

Skill Development
Heavy emphasis on critical thinking, complex problem-solving, project management, and scientific communication.

Networking Opportunities
Close collaboration with faculty experts and research peers creates valuable professional connections.

Graduates are equipped with advanced skills highly valued in both academia and the tech industry. Potential roles include:

• Senior Research Scientist
• Academic Lecturer / Professor
• AI & Machine Learning Engineer
• Specialised Technical Consultant
• Data Architect
• R&D Software Lead