Bachelor in Computer Science (Honours)(Data Analytics)
Programme Overview
This programme is designed to prepare students for a career in computer science with a focus on data analytics by providing a strong foundation in programming, data science, and analytical techniques. Students will learn to process, analyse, and interpret complex datasets, applying tools such as machine learning, AI, and predictive modelling. They will gain practical experience through hands-on projects and real-world data applications. The students will gain the skills and knowledge to pursue careers as data analysts, data scientists, or in other advanced computing roles.
- Industry-Ready Career Pathways
A structured, industry-aligned curriculum in data science and analytics with progressive learning and internship opportunities. - Immersive Learning Experience
Hands-on, industry-linked learning through projects, hackathons, lectures, expos, and research collaborations, enriching students beyond the classroom. - Global Exposure
Opportunities include overseas study and exchange programmes with partner universities. This exposure strengthens global awareness and career prospects. In addition, industry-linked certifications through partnerships such as Huawei ICT Academy, students gain both credibility and connections that matter. - Future-ready innovators
Curriculum in emerging tech fields fosters adaptability, leadership, and innovation, producing graduates who are problem-solvers, tech leaders, and innovators.
Progression Pathways
Graduates of the Bachelor of Computer Science (Honours) (Data Analytics) can progress to postgraduate studies by coursework or research, such as:
- Master of Computer Science (by coursework)
- Master of Science in Engineering (by research)
While MILA currently offers progression in these areas, graduates are also well-prepared to pursue advanced studies in artificial intelligence, cybersecurity, data science, cloud computing, software engineering, and other computing-related disciplines at universities locally or internationally, providing flexibility to specialise further and advance careers in cutting-edge technology sectors.
Entry Requirements
| MATRICULATION/FOUNDATION | Pass with a minimum CGPA of 2.00 and a Credit in SPM including Additional Mathematics or Mathematics and any one of the Science, Technology, or Engineering subjects |
| STPM (Arts Stream) | Pass with a minimum grade of C (GP 2.00) in any two (2) subjects and a credit in SPM including Additional Mathematics or Mathematics and one Science/Technology/Engineering subject |
| STPM (Science Stream) | Pass with a minimum grade of C (GP 2.00) in Mathematics and one (1) Science or ICT subject |
| STAM | Pass with a minimum grade of Jayyid in any two (2) subjects and a credit in SPM including Additional Mathematics or Mathematics and one Science/Technology/Engineering subject |
| DIPLOMA | Pass a Diploma in Science and Technology (Level 4, MQF) in a related field with a minimum CGPA of 2.75, or a CGPA of 2.50 subject to rigorous assessment |
| DIPLOMA KEMAHIRAN MALAYSIA (DKM) /
DIPLOMA VOKASIONAL MALAYSIA (DVM) / DIPLOMA LANJUTAN KEMAHIRAN MALAYSIA (DLKM) |
Pass with a minimum CGPA of 2.50 subject to HEP Senate / Academic Board approval |
| OTHERS | Other equivalent qualifications recognised by the Malaysian Government |
English Requirement
| MUET | Band 3 |
| IELTS | 5.0 |
| TOEFL | 60 |
| Others | Pass |
Programme Structure
Year 1
- Computer Graphics
- Computer Organisation and Architecture
- Computer Programming
- Database Management System
- Discrete Mathematics
- English for Professional Communication
- Internet and Web Programming
- Probability and Statistics
- Professional Computing Practices.
Year 2
- Computer Network (H)
- Data Structures and Algorithm (H)
- Data Warehousing & Data Mining
- E-Commerce
- Human Computer Interaction (H)
- Introduction to Psychology
- Java Programming
- Management Information Systems
- Object-Oriented Programming
- Operating Systems
- Server-Side Programming
- Software Engineering
- Software Testing and Quality Assurance
Semester 3
- Artificial Intelligence (H)
- Big Data (H)
- Data Analytics
- Data Science
- Entrepreneurship
- Final Year Project 1
- Final Year Project 2
- Industrial Training*
- Machine Learning
- Mobile Computing
- Natural Language Processing
- Predictive Analytics and Modelling
- Project Management
- System Analysis and Design
Mata Pelajaran Umum (MPU)
- Bahasa Kebangsaan A** / Introduction to Psychology*
- Bahasa Melayu Komunikasi 2 (Non-Malaysian) / Penghayatan Etika dan Peradaban (Malaysian)
- Integrity and Anti-corruption
- Philosophy and Current Issues
(H) – Embedded with Huawei ICT Academy modules, integrating 4 Huawei General Courses and 1 Huawei Certified ICT Associate–AI professional certification.
*In Year 3, students will need to undergo a minimum 12 weeks of industrial training.
Courses and assessments may change due to curriculum updates. For the latest information, please consult our counsellors.
Notes
*For students (including Non-Malaysian) who are not required to take Bahasa Kebangsaan A .
**For Malaysian students who did not achieve credit for Bahasa Melayu in Sijil Pelajaran Malaysia (SPM).
Assessment
- Continuous assessments and final examination
- Face-to-face lecture sessions and lab practical
Future Pathways
Areas of Application
- Fraud detection
- Recommendation systems
- Predictive maintenance
- Natural language processing
- Cybersecurity threat detection
Career Opportunities
- Data Scientist
- Machine Learning Engineer
- Data Analyst
- AI Researcher
- Business Intelligence Analyst
Get in touch with us now
Interested in joining our programme? Fill out the form below to submit your enquiry. Our admissions team will review your information and get back to you shortly to discuss the next steps in your application journey.
