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Bachelor of Science (Honours) in Applied Artificial Intelligence

Faculty of Artificial Intelligence and Engineering (FAIE)

(N/0611/6/0107, MQA/PSA 18303)

The Bachelor of Science (Honours) in Applied Artificial Intelligence, BScAAI is a 3-year programme designed to equip students with the knowledge and skills to develop AI-powered solutions that drive innovation across industries. This programme focuses on the application of AI in automation, data intelligence, and smart decision-making systems, preparing graduates to lead the AI revolution in various sectors.

BScAAI uniquely combines AI engineering principles with core areas such as IoT, cloud computing, digital system design, machine vision, and embedded AI solutions, ensuring students gain practical knowledge in designing intelligent, scalable, and high-performance AI-driven systems. With hands-on laboratory-based courses, real-world industrial collaborations, and applied research projects, students will develop technical skills required for the next generation of AI engineers, robotics specialists, and intelligent systems developers.

With a strong emphasis on real-time AI deployment, optimization of AI models for hardware implementation, and the integration of AI in edge computing, industrial automation, and cyber-physical systems, graduates will be well-prepared for careers as AI Engineers, Embedded AI Developers, Robotics and Perception Specialists, IoT and AI Solutions Architects, and Intelligent Systems Designers.

Aligned with MMU’s strategic direction, this programme is designed to bridge AI research with engineering applications, ensuring that graduates contribute to solving real-world problems in sectors such as smart cities, healthcare, autonomous systems, precision agriculture, and advanced robotics. By integrating AI with engineering fundamentals, this programme equips students with the ability to develop sustainable, efficient, and transformative AI technologies for the future.

        1. Pass Foundation / Matriculation studies with a minimum of CGPA of 2.00 from a recognised institution AND a Credit in Mathematics at SPM Level or its equivalent*; OR
        2. Pass STPM or its equivalent with a minimum Grade C (GP 2.00) in any TWO (2) subjects AND a Credit in Mathematics at SPM Level or its equivalent*; OR
        3. Pass A-Level with a minimum of Grade D in any TWO (2)subjects AND a Credit in Mathematics at SPM Level or its equivalent*; OR
        4. Pass UEC with a minimum of Grade B in at least FIVE (5) subjects (inclusive of Mathematics* and English); OR
        5. Pass STAM with a minimum grade of Jayyid in any TWO (2) subjects AND a Credit in Mathematics at SPM Level or its equivalent*; OR
        6. Diploma in Computing (Level 4, MQF) or equivalent with a minimum CGPA of 2.50. Candidates with a CGPA below 2.50 but more than 2.00 may be admitted subject to a thorough rigorous assessment; OR
        7. Diploma (Level 4, MQF) in Non-Computing with a minimum CGPA of 2.75 AND a Credit in Mathematics at SPM Level or its equivalent*. Candidates with a CGPA below 2.75 but more than 2.50 can be admitted subject to a through rigorous assessment; OR
        8. Pass DKM /DLKM/DVM in Computing fields with a minimum CGPA of 2.50 subjected to HEP Senate / Academic Board’s approval**; OR
        9. Other relevant & equivalent qualifications recognised by the Malaysian Government. (Candidates can be admitted if their admission qualification contains Mathematics subject(s) equivalent to Mathematics at the SPM level. If it is not equivalent, the reinforcement Mathematics subject equivalent to the SPM level must be offered in the first semester or before enrolment with unconditional offer); OR
        10. Possess an APEL.A certificate from MQA for admission into Bachelor programmes. For more information, please visit https://www.mmu.edu.my/apel-a/

NOTE

*Candidates with a pass in Mathematics at SPM level need to take and pass the reinforcement Mathematics subject that is equivalent to the SPM level. The reinforcement Mathematics subject must be offered in the first semester or before enrolment with unconditional offer.

**DKM/DLKM/DVM candidates may be required to undergo Bridging Programme as an additional requirement.

Students are required to pass the reinforcement Mathematics before being allowed to take related core courses. The candidate can sit for any subjects that did not indicate Mathematics as a prerequisite.

Reinforcement Mathematics can contribute to the overall graduating credit.

Students from Matriculation / Foundation or its equivalent can be exempted from taking reinforcement Mathematics, provided that the Mathematics offered at that programme level is equivalent / more than the Mathematics offered at an SPM level.

 

    • Programme Structure
      • Core
        • Year 1
          • Computer Architecture and Organisation
          • Data Communications and Networking
          • Artificial Intelligence Fundamentals
          • Computer Programming
          • Database Systems
          • Operating Systems
          • System Analysis and Design
          • Ethics and Professional Conducts
          • Discrete Mathematics and Probability
          • U2
          • U3
          • U4
          • Character Building
          • Sustainable Society
          • Fundamentals of Digital Competence for Programmers
        • Year 2
          • Applied Electronics & Practical Techniques
          • Digital System Design with FPGA
          • Machine Learning Concepts and Technologies
          • Mathematics for AI (Linear Algebra, Linear and Non-Linear Optimisation)
          • Algorithms and Data Structures for AI
          • Bespoke Industrial Studio
          • Data Analytics Fundamentals
          • Embedded Systems for AI
          • Machine Vision and Image Processing (4 CH)
          • Digital Fabrication and Prototyping
          • Project Management for AI Applications
          • BYOC 1
          • BYOC 2
          • U1
        • Year 3
          • Natural Language Processing
          • Robotics & Perception
          • Deep Learning and Generative AI Technology
          • Cloud Computing Technology
          • AI in Autonomous Systems
          • IoT Systems and Applications
          • Industrial Training
          • Project I
          • Project II
          • BYOC 3
          • U1
      • Elective Modules
        • Four (4) subjects should be taken from the following:
          Consumer Trends
          Creativity and Innovation
          Becoming A Leader
          Corporate Training
          Professional Image and Etiquette
          Corporate Communication
          Corporate Strategy
          Design Thinking for Strategic Communication
          Social Media Strategies
          Film Appreciation
          Basic Filmmaking
          Suspenseful Filmmaking
          Fundamental of Wireless Communications
          Communications Networks
          Radio Network Planning Towards 5G
          Internet & Mobile Application
          Media Anthropology
          Media Law
          Project Management
          Motion Capture
          Information Visualization
          Visual & Corporate Identity
          Accounting for Decision Making
          Personal Finance
          Fundamentals of Marketing
          Digital Transformation Strategy
          Digital Transformation Technologies
          Ergonomics and Human Factor
          Machine Vision
          IoT Design and Interfacing
          Radio Network Planning Towards 5G
          Digital Busine
          Business Information Systems
          Data Analytics for Businesses
          Cyber Security
          Understanding Management
          Fundamentals of Marketing
          Financial Management
          Data Analytics for Businesses
          Business Risk Management
          Consumer law
          Labour Law
          Law and Economics
          Environmental Law
          Law of Banking
      • University Subjects
        • U2 – Bahasa Kebangsaan A or Foreign Language Beginners
          U1 – Falsafah dan Isu Semasa (Local & International)
          U4 – Co-Curriculum
          U1 – Penghayatan Etika dan Peradaban (Local) or BM Komunikasi II (International)
    • Career Prospects
        1. AI Specialist – Develops and applies AI-driven solutions for industrial automation, robotics, and intelligent systems.
        2. Machine Learning Developer – Designs, trains, and deploys machine learning models for various real-world applications.
        3. Embedded AI Developer – Specializes in implementing AI in embedded systems, IoT devices, and smart automation technologies.
        4. Robotics and Perception Specialist – Works on AI-powered autonomous systems, machine vision, and intelligent control applications.
        5. IoT and AI Solutions Developer – Creates AI-enhanced IoT applications for smart cities, industrial monitoring, and automation.
        6. Data Science Practitioner – Analyzes and interprets data using AI and analytics to support data-driven decision-making.
        7. Computer Vision Specialist – Develops AI-based image processing and machine vision solutions for automation, security, and healthcare.Graduates of the Bachelor of Science (Honours) in Applied Artificial Intelligence  program will have diverse career opportunities in industries that integrate AI with automation, robotics, and engineering technology. Potential career paths include:
        8. AI Solutions Consultant – Advises businesses on integrating AI technologies to improve efficiency, automation, and innovation.