Bachelor of Computer Science in Artificial Intelligence | Page 2

WHAT YOUR COURSE WILL LOOK LIKE 5

Part A. Foundation studies Part B. Professional practice studies Part C. Specialist studies Part D. Applied studies Part E. Free elective studies Industrial training( compulsory MQA requirement for students who do not participate in the IBL program)

Approved technical elective units FIT3192 Emerging and advanced topics in artificial intelligence FIT3183 Malicious AI and dark side security

Course structure

Part A. Foundation studies( 42 Credit points) This study will develop your understanding of the role and theoretical basis of computer science, computational methods and the core principles that underpin modern AI.

Part B. Professional practice studies( 6 Credit points) This study develops professional skills by providing an understanding and appreciation of the ethical and professional guidelines that apply to computer science and the responsible use of AI. It builds your ability to work as an effective team member, communicate proficiently and appropriately in professional settings. You will also develop an awareness of ethical AI practices, including fairness, accountability and the societal impact of intelligent systems.

Part C. Specialist studies( 36 Credit points) This study will develop your in depth knowledge of advanced computer science and AI, focusing on the specialised methods, models and analytical approaches used in contemporary AI practice.

Part D. Applied studies( 12 Credit points) This study integrates and consolidates your knowledge through applied practice in a computer science or AI project. You will complete a project related to your specialisation, along with either the industry based learning placement or the industry work experience unit.

Part E. Free elective studies( 48 Credit points) This study enables you to broaden and deepen your knowledge of computer science through elective units in areas such as data science, data analytics, parallel computing, cloud computing and advanced data structures and algorithms. You may also select units from across the University in which you are eligible to enrol.

What you ' ll learn

This course immerses you in the core ideas and advanced methods that shape modern artificial intelligence.

You will explore symbolic AI, machine learning, neural networks, computer vision, natural language processing, generative intelligence and cutting edge areas such as intelligent agents and neuro-symbolic AI.

You will also learn how to apply theory and practice to design ethical and intelligent software systems that address real challenges across a wide range of industries.

Industry experience

Gain hands-on industry experience through an internship or industry-based learning( IBL) program. IBL offers high-performing students the opportunity to participate in placements at top IT companies. Alternatively, you’ ll complete a 12-week internship after your second year, which will give you a strong foundation and framework for experiential learning.

Entry requirements 6

Prerequisites English: Monash’ s minimum requirements apply.

Higher level Mathematics: Australian Year 12 equivalent

5 This course map is intended as a rough guide. Units listed may vary depending on intake, availability and the latest requirements. 6 According to the MQA Program Standards, only Diploma applicants who completed a Diploma in Science and Technology or a Diploma in Computing fields can be considered for enrolment into a bachelor’ s degree in computer science. 7 The Malaysian Qualification Agency( MQA) accepts a minimum D Grade in A Level to be equivalent to the STPM Pass grade. 8 The undergraduate entry requirements published in this guide are for students who commenced the MUFY program in 2025. 9 Monash College Diploma Part 2 provides a pathway into the second year of the corresponding undergraduate studies. The entry requirements published in this guide are for students commencing their undergraduate destination degree in 2026.

monash. edu. my / bachelor-computer-science-ai

The information in this flyer was correct at the time of publication. Monash University Malaysia reserves the right to alter this information should the need arise. Produced by Marketing and Future Students, Monash University Malaysia. November 2025

Monash University Malaysia Registration No. 199801002475( 458601-U) DULN002( B)

Help us to reduce waste.

Scan to download a digital copy of this flyer.

Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia monash. edu. my mum. enquiry @ monash. edu + 603 5514 6000