PROGRAMME REVIEW
Data is essential for organizational success, with modern data systems critical for handling the vast and complex data of today’s digital era. Traditional methods are inadequate, necessitating advanced data systems across all types of organizations. Data Science, a field that extracts valuable insights from data, has wide applications and offers significant opportunities for improving global quality of life. This program prepares graduates for the digital age by providing hands-on experience through internships and practical courses. These components ensure students gain industry-relevant skills and networking opportunities, enhancing their employability. The program is supported by experienced local and international faculty.
Entry Requirement
STPM or equivalent
- Minimum Grade C (CGPA 2.00) in any 2 subjects and credit in Additional Mathematics or Mathematics and any 1 Science, Technology or Engineering subject at SPM or equivalent.
STPM or equivalent (Science Stream)
- Minimum Grade C (CGPA 2.00) in any 1 Mathematics subject and 1 Science or ICT subject.
Foundation/ Matriculation or equivalent (Non-Science Stream)
- Minimum CGPA of 2.00 and credit in either Additional Mathematics or Mathematics and any 1 Science, Technology or Engineering subject at SPM Level or equivalent.
Diploma in ICT or Science and Technology related field
- Minimum CGPA of 2.50 (Candidates with CGPA below 2.50 but above 2.00 may be admitted subject to rigorous internal assessment process).
Others
- Other equivalent qualifications recognised by Perdana University’s Senate
Programme Structure
List of course/module offered in the programme;
Year 1
- Calculus
- Discrete Mathematics
- Introduction to Computer Programming
- Computer Organisation & Operating System
- Data Structures and Algorithm
- Probability and Statistics
- Linear Algebra
- Fundamentals of Software Development
- Introduction to Database
- MPU subjects
Year 2
- Computer Network
- Applied Regression and Time-Series Analysis
- Web Programming and Scraping
- Seminar and Industry talks: Current Topics in Data Science
- Introduction to Data Science and its Toolkits
- Big Data
- Multivariate Analysis
- Introduction to Parallel Processing
- Data Analytics Essentials
- Research Methodology, Critical Thinking and Scientific Communication
- MPU subjects
- Elective*
Year 3
- Business Intelligence & Entrepreneurship
- Dimensionality Reduction
- Machine Learning
- Professional Ethics and Information Law
- Elective*
- Visualisation on Data & Communicating Results
- Final Year Project
- Internship
- Electives
- Digital Marketing
- Data Mining Application in Life Sciences
- Health Analytics and Data Mining
- Econometrics
- Data Driven Organisation
Study Pathway
Career Opportunities;
Data Science graduates are in demand for various jobs in many sectors and industries ranging from education, finance, banking, business, corporate, social science, telecommunication, life sciences, printing education, film/animation, web analytics, broadcasting, and advertising, among many others. The plethora of professions offered in the data industry includes Information Systems Auditors, Information Systems Consultants, Information Technology Consultants, Data Analysts/Professionals, Database Programmers, Web Programmers, Application Software Consultants, and System Analysts among others.
Unique Features
Recognition & Accreditation:
- This programme is provisionally by the Malaysian Qualifications Agency (MQA) and recognised by the Ministry of Education (MOE).
Teaching & Learning Method:
- Blended learning (lecture combined with online learning and independent study), practical, tutorial, internship, assignment, presentation, and test.
- Scholarships available
- Personalised learning experience
- Equipped with trending skills
- Soaring industry demand.
- Boundless job opportunities, locally and internationally.
- Lifeline for Industrial Revolution 4.0.
- Balanced curriculum.
- Access to international data science network.
- Diverse and enriching industry placement experience.
- Associateship to data science support ecosystem.
