Bachelor of Science (Honours) in Applied Artificial Intelligence

(N/0611/6/0107)/ 01/30 (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.

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• Entry Requirements
  • 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
        • Fundamentals of Computer Systems
          Data Communications and Networking
          Artificial Intelligence Fundamentals
          Fundamentals of Computer Science
          Database Systems
          Digital Fabrication & Prototyping
          Data Acquisition, Engineering and Visualization
          AI Governance & Ethics
          Probability & Statistics
      • Year 2
        • Applied Electronics & Practical Techniques
          Software Engineering
          Machine Learning Concepts and Technologies
          Mathematics for AI
          Algorithms and Data Structures for AI
          Bespoke Industrial Studio
          Data Analytics Fundamentals
          Embedded Systems for AI
          Machine Vision and Image Processing
          Project Management for AI Applications
          BYOC 1
          BYOC 2
      • 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
    • BYOC Electives
      • March/April
        Fundamentals of Marketing
        Digital Transformation Strategy
        Personal Finance
        Radio Network Planning Towards 5G
        Media Anthropology
        Project Management
        Motion Capture
        Media Law
        Corporate Strategy
        Social Media Strategies
        Introductory Mobile Application Development
        Basic Filmmaking
        Fundamental of Wireless Communications
        Radio Network Planning Towards 5G

        October/November
        Design Thinking for Strategic Communication
        Corporate Communication
        Suspenseful Filmmaking
        Communications Networks
        Introductory Data Science
        Introductory Data Visualization
        Visual and Corporate Identity
        Information Visualization
        Principal of Finance
        Fundamental of Marketing

    • University Subjects
      • Character Building Program: Character Building and Sustainable Society
        Fundamentals of Digital Competence for Programmers
        U1: Falsafah dan Isu Semasa
        U1: Penghayatan Etika dan Peradaban Isu Semasa (Local Students)/Bahasa Melayu Komunikasi 2 (International Students)
        U2: Bahasa Kebangsaan A/Foreign Language
        U3: Integrity and Leadership
        U4: Co-Curriculum
    • Career Prospects
      • AI Specialist, Machine Learning Developer, Embedded AI Developer, Robotics and Perception Specialist, IoT and AI Solutions Developer, Data Science Practitioner, Computer Vision Specialist, AI Solutions Consultant