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Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

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+60142521561

EasyUni Sdn Bhd

Level 17, The Bousteador No.10, Jalan PJU 7/6, Mutiara Damansara 47800 Petaling Jaya, Selangor, Malaysia
4.4

(43) Google reviews

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Bachelor of Science (Honours) Intelligent Robotics

Course overview

Statistics
Qualification Bachelor's Degree
Study mode Full-time
Duration 3 years
Intakes April, July, October
Tuition (Local students) $ 14,877
Tuition (Foreign students) $ 20,021

About

The Bachelor of Science (Honours) Intelligent Robotics is a 3-year programme that strikes on exquisite balance between the fundamentals of engineering and hands-on, practical skills. This unique multi-disciplinary program combines electronics, robotics, artificial intelligence, automation, and computer programming. It adopts a modern learning approach with early exposure to real world applications. Graduates will be agile knowledge workers in the IR4.0 age and beyond, highly sought after by the industry.

Career Prospects:

  • Robotics System Designer/Programmers
  • AI and Machine Learning Developer
  • Embedded System Designer
  • Control and Automation Specialist
  • Field Application Technologist
  • Printed Circuit Board (PCB) Designer
  • Production and Planning Engineer
  • Industry 4.0 Technologist

Admissions

Intakes

Fees

Tuition

$ 14,877
Local students
$ 20,021
Foreign students

Estimated cost as reported by the Institution.

Application

$ 0
Local students
$ 0
Foreign students

Student Visa

$ 665
Foreign students

Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.

Entry Requirements

  1. Pass Foundation / Matriculation studies in related field from a recognised institution with a minimum CGPA of 2.50; OR
  2. Pass STPM or its equivalent with a minimum Grade C (GP 2.00) in any 3 subjects inclusive of Mathematics and Physics; OR
  3. Pass A-Level with a minimum of Grade D in any three (3) subjects inclusive of Mathematics and Physics; OR
  4. Pass UEC with a minimum of Grade B in at least five (5) subjects inclusive of Mathematics and Physics; OR
  5. Recognised Diploma in the related field with a minimum CGPA of 2.50 or its equivalent;* OR
  6. Pass DKM /DLKM/DVM with a minimum CGPA of 2.50. Candidates with CGPA below 2.50 MUST have at least two (2) years of work experience in the related field.**

Note
*Candidates with CGPA below 2.50 but above 2.0 may be admitted subject to a rigorous internal assessment process.
**DKM /DLKM/DVM candidates may be required to undergo Bridging Programme as an additional requirement.

Curriculum

Core Subjects

Year 1 

  • Engineering calculus
  • Computer and programming
  • Micro-controllers & microprocessors
  • Electrical circuits
  • Basic electronics
  • Differential equations
  • Digital design
  • Linear algebra and numerical methods
  • Rapid modelling
  • Analog electronics

Year 2

  • Linear systems & signals
  • Electromagnetics with applications
  • Electrical machines and power systems
  • Robotics – Machine design and mechanisms
  • Introduction to artificial intelligence
  • Actuators and sensors
  • Electronics instrumentation
  • Robotics – Modelling and control
  • Feedback control
  • Advanced programming
  • Internship

Year 3

  • Mobile robots and drones
  • Machine learning concepts and technologies
  • Project I
  • Project II
  • Machine vision & image processing

Electives

Hardware Track

  • IOT systems & applications
  • Electronic prototyping and PCB layout
  • Making embedded systems
  • Industrial automation and digital control
  • Signal and power integrity

Software Track

  • Cybersecurity
  • Software engineering fundamentals
  • Introduction to data science
  • Neural networks and deep learning
  • Robot programming

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