91吃瓜

Course Overview

This programme is curated specially to address the need for jobs that demand skills in the area of Artificial Intelligence (AI). It encompasses the learning of AI, Computer and Engineering. By espousing these areas, students can expect to grasp a keen understanding of the technology, its history, functionality and challenges in the application of AI. This programme covers the core theoretical foundations and provides advanced algorithmic, statistical and computer engineering knowledge.

Essentially, students will be exposed to the design, modeling, analysis, and applications of AI through machine vision, language, signal processing and robotics. As students develop the adroitness in this field, gain new insights and smarter correlations, they will appreciate their transformation in the higher-order professional the industry needs.

Curriculum

Year 1

• Mathematical Methods for Engineers I
• Circuit Theory I 
• Electromagnetic Theory 
• Engineering Graphics and Design 
• Computing for Engineers
• Mathematical Methods for Engineers II
• Analogue Electronics I 
• Digital Electronics I
• Statistics
• Electrical and Electronic Lab 1
• Computer Architecture
• Technical Communication

Year 2

• Circuit Theory II
• Instrumentation and Measurement 
• Electrical Power
• Algorithm Design and Analysis 
• Object Oriented Programming 
• Safety, Health and Environment 
• Introduction to Artificial Intelligence 
• Software Engineering
• Java Programming
• Electrical and Electronic Lab 2 
• Computer Engineering and AI Lab
• Industrial Training I

Year 3

• Digital Signal Processing 
• Engineering Management and Economics
• Microprocessor Systems 
• Data Communication and Networks 
• Embedded System Design 
• Control Systems 
• Engineers in Society
• Communication Theory
• Machine Learning 
• Human Computer Interaction
• Instrumentation and Control Lab
• Industrial Training II

Year 4

• Integrated Design Project 1 
• Operating Systems 
• Cybersecurity
• Integrated Design Project 2 
• Elective 1
• Elective 2 
• Elective 3 
• Final Year Project A*
• Final Year Project B

Elective Courses (Select 1 specialisation only)

Specialisation 1: Business Analytics
Data Mining
Database Systems
Big Data

Specialisation 2: Computational Intelligence
Big Data
Machine Vision
Blockchain

Specialisation 3: Control and Intelligent System
Parallel Computing
Mobile Application Development
Advanced Instrumentation and Control

Entry Requirements

Academic Requirements

?STPM

Minimum 2Cs including Mathematics and one relevant Physical Science subject

A Level

Minimum 2Ds including Mathematics and one relevant Physical Science subject

?UEC

Minimum 5Bs including Mathematics and one relevant Physical Science subject

?CPU

Minimum average of 60% in 6 subjects, inclusive of a minimum score of 60% in Mathematics and one relevant Physical Science subject

?Local Matriculation

Minimum CGPA 2.0

?Foundation from other University/ College

Minimum CGPA 2.0

WAEC/NECO

A maximum aggregate of 15 points out of best 5 subjects, inclusive of minimum B in Mathematics and one relevant Physical Science subject

Diploma/ Advance Diploma/ equivalent

Minimum CGPA 2.0

• Subject to Faculty discretion after reviewing transcript and syllabus. Max credit transfer of 30% of the programme total credits

Other qualifications deemed equivalent to STPM/A-Level by Malaysian Qualifications Agency

Minimum overall average of 60%, inclusive of minimum 60% in Mathematics and one relevant Physical Science subject

International Baccalaureate

Minimum 26/42 points from 6 subjects (inclusive Mathematics and one relevant Physical Science subject)

SAM

Minimum average of 60% in 5 subjects, inclusive of minimum scores of 60% in Mathematics and one relevant Physical Science subject

SACE/AUSMAT/TEE/SAM

Minimum ATAR score of 60% AND minimum score of 60% in Mathematics AND one relevant Physical Science subject
OR
Minimum overall average of 60% in 5 subjects AND minimum score of 60% in Mathematics AND one relevant Physical Science subject

WACE/NTEC

Minimum overall average of 60%, inclusive of minimum 60% in Mathematics and one relevant Physical Science subject

English Language Requirements

For Local Students

MUET

Band 3.5

SPM English Language

Grade B+

SPM English Language 1119/O-Level/IGCSE

Grade C

UEC English Language

Grade A2

CEFR

B1 (High B1)

• In the event that the English language requirements are not met, applicants will be required to take the Basic English and English Foundation for in-sessional academic enhancement concurrently with the programme.

For International Students

154

IELTS

Band 5.0

Cambridge English Qualifications and Tests

154

TOEFL IBT

40

TOEFL ESSENTIALS (ONLINE)

7.5

Pearson Test of English

47

MUET

Band 3.5

CEFR

B1 (High B1)

• International applicants who do not meet the respective academic programme’s English Language Requirement will need to improve their proficiency by enrolling into the English for Tertiary Education programme (R/KJP/00920-00929) which helps them prepare for attaining a required band score. Placement into the various levels of the English for Tertiary Education programme depends on the English Language qualification students have at the point of admission and/or the outcome of the English Placement Test.
• **The applicants who have met the respective academic programme’s English Language Requirement may be advised by Faculty to improve their proficiency by undertaking the additional English proficiency courses.

Career Prospects

This programme provides students with a solid foundation in computer engineering and AI, including the electronics behind AI systems. It prepares graduates for various careers in advanced technologies, helping them succeed in traditional AI roles and emerging Responsible AI specialist positions in a rapidly expanding market. Graduates are prepared to pursue career opportunities in the following roles:

• Data Engineer (Machine Learning Specialist)
• Artificial Intelligence Application Engineer
• AI Applied Researcher
• Computer Vision Engineer
• Artificial Intelligence Engineer
• Machine Learning Engineer
• AI Control System Engineer
• AI Research Scientist
• AI Software Engineer
• Intelligence System Engineer
• Computer System Engineer
• Computer Hardware Engineer
• Programmer
• Electronic Engineer
• Academician
• Internet of Things (IoT) System Engineer