Total Fees

RM40,700

  • Level

    Postgraduate

  • Duration

    2.5 year(s)

  • Study Mode

    Online

  • Major

    Computing & IT

  • Campus

    Bukit Jalil, Kuala Lumpur

  • Certification

    Asia Pacific University of Technology and Innovation (APU)

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Description

The Master of Science in Artificial Intelligence (ODL) is a postgraduate programme designed to equip students with advanced knowledge and practical skills in artificial intelligence, preparing them for careers in AI-driven industries or progression into advanced research and development roles. The programme covers essential areas such as machine learning, deep learning, data analytics, computer vision, natural language processing, and intelligent systems, combining theoretical foundations with practical implementation. Delivered through Open and Distance Learning (ODL), it offers flexibility for working professionals while maintaining strong academic rigor and industry relevance. Through hands-on projects, case studies, and research-based learning, students develop technical proficiency, analytical thinking, and problem-solving abilities essential for designing and deploying AI solutions in real-world environments. The programme emphasises innovation, technological advancement, and global perspectives, ensuring graduates are well-prepared to pursue careers as AI specialists, data scientists, machine learning engineers, or to advance into further academic research in artificial intelligence and related fields.

Intake Month(s)

June, August

Application Fee RM 800.00
Refundable Deposit RM 500.00
Tuition Fee RM 39,400.00
Grand Total RM 40,700.00

Course Structure

  • Pre-Requisite Modules (for non-computing students)
  • Programming in Python
  • Database Fundamentals
  • Fundamentals in Artificial Intelligence
  • Common Modules
  • Artificial Intelligence
  • Image Processing and Computer Vision
  • Fuzzy Logic
  • Applied Machine Learning
  • Computational Intelligence Optimization
  • Natural Language Processing
  • Research Methodology in Computing and Engineering
  • Project Paper
  • Elective 1
  • Elective 2
  • Elective 3

  • Choose 3
  • Applied Robotics
  • Pattern Recognition
  • Expert Systems and Knowledge Engineering
  • Business Intelligence Systems
  • Multivariate Methods for Data Analysis
  • Deep Learning

Entry Requirement

  • Successful completion of a relevant Bachelor Degree programme in computing with CGPA 2.50, or its equivalent qualification as accepted by the Senate
  • Successful completion of a relevant Bachelor Degree programme in computing with CGPA 2.00 and not meeting a CGPA of 2.50 can be accepted, subject to a rigorous internal assessment
  • Successful completion of a Bachelor Degree programme in non-related fields with CGPA 2.00 as accepted by the Senate and with relevant working experience, subject to a rigorous internal assessment
  • Successful completion of a Bachelor Degree programme in non-related fields with CGPA 2.00 as accepted by the Senate and without relevant working experience, subject to passing pre-requisite courses
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