Programme Overview
Programme Aims
The programme will help students to become professionals with good skills to program and design intelligence system in the job market. Besides this, the programme also promote the competitive power of Malaysia in artificial intelligence, which could boost the technology and economics of this nation among China, ASEAN counties and even the whole international community.
Programme Educational Objectives (PEO)
The PEOs are to produce graduates who:-
PEO1 | Process and comprehend the knowledge, principles and skills in artificial intelligence, including the intelligence theories, practical models and system design methodologies. |
PEO2 | Possess analytical and critical thinking skills to solve problems by applying knowledge, principles, skills in artificial intelligence. |
PEO3 | Able to apply fundamental mathematical, scientific, engineering, legal and theoretical computing knowledge in analyzing, modelling, designing, developing and evaluating computing solutions and artificial intelligence models. |
PEO4 | Understand the interplay between theory and practice of artificial intelligence and the essential links between them, then develop the consciousness and ability of lifelong learning and the basic leadership ability of management. |
Programme Structure
YEAR 1 | |||||||||||
SEMESTER 1 (18 WEEKS) | SEMESTER 2 (18 WEEKS) | SEMESTER 3 (6 WEEKS) | |||||||||
Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value |
Calculus I A | BSC121 | Common Core | 5 | Calculus II | BSC123 | Common Core | 5 | Bahasa Melayu Komunikasi /Penghayatan Etika dan Peradaban | MPU1.1-I / MPU3182 | Compulsory | 2 |
Linear Algebra | BSC124 | Common Core | 3 | Probability and Statistics A | BSC125 | Common Core | 4 | Bahasa Kebangsaan A / Writing for Professional Purposes | MPU2.1 / MPU2.2 | Compulsory | 2 |
Programming Language C | AIT101 | Common Core | 3 | Principles of Artificial Intelligence | SOF106 | Major Core | 3 |
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Python and Tensorflow Programming | AIT102 | Common Core | 3 | Introduction to Intelligence Application | AIT103 | Major Core | 3 |
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Community Service | MPU4.1 | Compulsory | 2 | Select from Table 1b | Gxxxx | General Elective | 3 |
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TOTAL CREDIT VALUE | 16 | TOTAL CREDIT VALUE | 18 | TOTAL CREDIT VALUE | 4 |
YEAR 2 | |||||||||||
SEMESTER 1 (18 WEEKS) | SEMESTER 2 (18 WEEKS) | SEMESTER 3 (6 WEEKS) | |||||||||
Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value |
Discrete Mathematics B | BSC136 | Common Core | 3 | Principles of Operating Systems | CST306 | Common Core | 4 | Intoduction to the Constitution of Malaysia | MPU3.1 | Compulsory | 2 |
Data Structures | AIT206 | Common Core | 3 | Methods and Applications of Deep Learning | AIT202 | Major Core | 3 | Malaysian Studies 3 / Falsafah dan Isu semasa | MPU1.2-I / MPU3192 | Compulsory | 2 |
Applied Machine Learning | AIT201 | Major Core | 3 | Design and Analysis of Algorithms | CST207 | Common Core | 4 |
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Principles of Computer Composition | CST301 | Common Core | 4 | Students to choose ONE (1) course (Total 3 credits): |
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Matrix Analysis and Application | AIT205 | Common Core | 3 | Natural Language Processing | AIT203 | Major Elective | 3 |
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| Computer Vision and Robotics | AIT204 | Major Elective | 3 |
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| Students to choose ONE (1) course (Total 4 credits): |
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| Object-Oriented Programming-C++ | CST209 | Major Elective | 4 |
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| Object-Oriented Programming-Java | CST210 | Major Elective | 4 |
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TOTAL CREDIT VALUE | 16 | TOTAL CREDIT VALUE | 18 | TOTAL CREDIT VALUE | 4 |
YEAR 3 | |||||||||||
SEMESTER 1 (18 WEEKS) | SEMESTER 2 (18 WEEKS) | SEMESTER 3 (6 WEEKS) | |||||||||
Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value |
Computer Networks and Communication | CST309 | Common Core | 4 | Thesis I | AIT310 | Major Core | 3 | Select from Table 1b | Gxxxx | General Elective | 6 |
Advanced Machine Learning | AIT301 | Major Core | 3 | Students to choose ONE (1) course (Total 3 credits): |
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Statistical Learning | AIT302 | Major Core | 3 | Advanced Issues of Artificial Intelligence (Natural Language Processing) | AIT303 | Major Elective | 3 |
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Students to choose TWO (2) courses (Total 8 credits): | Advanced Issues of Artificial Intelligence (Computer Vision) | AIT304 | Major Elective | 3 |
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Computer Architecture | CST308 | Major Elective | 4 | Students to choose TWO (2) courses (Total 6 credits): |
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Compiler Principles | CST302 | Major Elective | 4 | Robot Kinematics and Dynamics | AIT305 | Major Elective | 3 |
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Numerical Methods | BSC128 | Major Elective | 4 | Deep Reinforcement Learning and Control | AIT306 | Major Elective | 3 |
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| Computational Cognitive Science | AIT307 | Major Elective | 3 |
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| Students to choose ONE (1) course (Total 3 credits): |
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| Information Security | SWE308 | Major Elective | 3 |
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| Technology and Application of Internet of Things | SWE403 | Major Elective | 3 |
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| Big Data Analytics | SWE404 | Major Elective | 3 |
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TOTAL CREDIT VALUE | 18 | TOTAL CREDIT VALUE | 15 | TOTAL CREDIT VALUE | 6 |
YEAR 4 | |||||||||||
SEMESTER 1 (18 WEEKS) | SEMESTER 2 (18 WEEKS) | SEMESTER 3 (6 WEEKS) | |||||||||
Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value | Name of Course | Code of Course | Classification | Credit Value |
Software Architecture and Development Environment | CST307 | Common Core | 4 | Industrial Training | AIT420 | Industrial Training | 6 | Select from Table 1b | Gxxxx | General Elective | 6 |
Thesis II | AIT410 | Major Core | 3 |
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Students to choose ONE (1) course (Total 4 credits): |
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Computer Graphics | CST305 | Major Elective | 4 |
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Software Engineering | CST401 | Major Elective | 4 |
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Principles of Database Systems | CST403 | Major Elective | 4 |
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Students to choose ONE (1) course (Total 3 credits): |
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Strategic Reasoning for AI | AIT401 | Major Elective | 3 |
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Planning Techniques for Robotics | AIT402 | Major Elective | 3 |
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Advanced Data Analysis | AIT403 | Major Elective | 3 |
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TOTAL CREDIT VALUE | 14 | TOTAL CREDIT VALUE | 6 | TOTAL CREDIT VALUE | 6 |