Bachelor of Engineering in Artificial Intelligence (Honours)
- Key Information
Course Name:
Bachelor of Engineering in Artificial Intelligence (Honours)
University Name:
Xiamen University Malaysia (XMUM)
Campus:
Selangor
Qualification:
Bachelor
Duration:
4 years
Intake:
February, April, September
IELTS:
Not Required
Study Mode:
On-campus
Study Type:
Full time study
Program Mode:
Coursework
Yearly Tuition Fees
| Year | Fee |
|---|---|
| 1st Year | MYR 29,000 |
| 2nd Year | MYR 29,000 |
| 3rd Year | MYR 29,000 |
| 4th Year | MYR 29,000 |
Other Fees
| Description | Fee |
|---|---|
| Application Fee | MYR 100 |
| International Student Fee (Including visa application & renewal) | MYR 2,500 |
| Registration Fee | MYR 200 |
| Security Deposit (Refundable) | MYR 1,000 |
Campus
Selangor
Qualification
Bachelor
المدة
4 years
Intake
February, April, September
IELTS
Not Required
Study Mode
On-campus
Study Type
Full time study
Program Mode
Coursework
Course Fee for International Students
Yearly Tuition Fees
| Year | Fee |
|---|---|
| 1st Year | MYR 29,000 |
| 2nd Year | MYR 29,000 |
| 3rd Year | MYR 29,000 |
| 4th Year | MYR 29,000 |
Other Fees
| Description | Fee |
|---|---|
| Application Fee | MYR 100 |
| International Student Fee (Including visa application & renewal) | MYR 2,500 |
| Registration Fee | MYR 200 |
| Security Deposit (Refundable) | MYR 1,000 |
Course Overview
The Bachelor of Science in Artificial Intelligence (Honours) at Xiamen University Malaysia (XMUM) operates as a sophisticated pedagogical framework designed to ground scholars in the epistemological foundations and transformative methodologies of systemic algorithmic governance and cognitive stewardship. This program facilitates an intellectual transition to executive-level technical proficiency by synthesizing the rigorous heritage of XMU’s intelligence science faculty—consistently ranked among the top ten in China—with applied neural and computational praxis, ensuring that candidates can navigate the multifaceted complexities of a global economy increasingly defined by intelligent automation. To address the high-fidelity demands of the hyper-competitive global technology sector, the curriculum is strategically engineered to bridge the technical divide between abstract brain functionality and industrial-scale system design. A pivotal feature of the program at XMUM is its focus on research-led innovation and visual intelligence, leveraging the breakthroughs of world-class researchers like Ji Rongrong in the field of computer vision. By integrating technical expertise with a focus on heuristic critical analysis, the curriculum fosters a sophisticated command of the programming paradigms and architectures required to maintain a competitive advantage in the modern AI race. Through intensive study of the theoretical and practical applications of intelligent systems, the program emphasizes the development of the “hard skills” required for high-level algorithm development, data synthesis, and autonomous system implementation. The pedagogy ensures that graduates possess the analytical fluency necessary to meet the soaring demand for designers of intelligent systems across nearly every facet of modern life. Ultimately, the program serves as a critical mechanism for professional and technological advancement, establishing the foundational competencies and innovative mindset necessary for graduates to thrive as AI architects and contribute meaningfully to the digital and cognitive evolution of society.
Curriculum
Programme Structure
| Year | Themes | Key Modules |
|---|---|---|
| Year 1 | Mathematics & Intelligence Foundations | Calculus, Linear Algebra, Principles of Artificial Intelligence, Python and Tensorflow Programming, Programming Language C, and Probability and Statistics. |
| Year 2 | Machine Learning & System Core | Applied Machine Learning, Methods and Applications of Deep Learning, Data Structures, Design and Analysis of Algorithms, Principles of Operating Systems, and Matrix Analysis. |
| Year 3 | Advanced Analytics & Robotics | Advanced Machine Learning, Statistical Learning, Deep Reinforcement Learning and Control, Robot Kinematics and Dynamics, Computer Networks and Communication, and Thesis I. |
| Year 4 | Strategic AI & Industry Integration | Strategic Reasoning for AI, Planning Techniques for Robotics, Software Architecture, Thesis II, and Industrial Training. |
| Major Electives | Specialized Applications | Natural Language Processing, Computer Vision and Robotics, Internet of Things (IoT), Information Security, Computer Graphics, and Advanced Data Analysis. |
Field of Research
N/A