Bachelor of Engineering in Data Science

The School of Computing and Data Science now offers a new Bachelor of Engineering in Data Science (Honours) degree. The curriculum is designed to meet the growing demand for data science graduates in numerous industries, including financial, commercial, industrial, medical, and public sectors. The program aims to develop global leaders with analytical skills to adapt to a rapidly changing world. It provides students with the necessary mathematical, statistical, and computational skills to solve complicated data problems. The curriculum aims to equip students with analytical and statistical skills to tackle complicated data challenges. Students will gain essential knowledge and abilities for success in their careers and can also choose to pursue postgraduate courses in related subjects at leading universities worldwide.

Note: The degree does not fall under the engineering fields listed on the Malaysian Board of Engineers registration.

Any of These:

• STPM (Science Stream): A pass in STPM with at least a Grade C (GP2.0) in Mathematics AND 1 Science/ICT subject.
• STPM (Non-Science Stream): A pass in STPM with at least a Grade C (GP2.0) in any 2 subjects AND a credit in Additional Mathematics in SPM or its equivalent.
• A-LEVEL: A pass in A-Level with at least a Grade D in any 2 subjects.
• UEC: A pass in UEC with at least a Grade B in 5 subjects.
• Foundation/Matriculation: A pass in Foundation / Matriculation with at least a CGPA of 2.0 out of 4.0.
• Diploma:
  • A pass in Diploma in Computing fields (Computer Science/Software Engineering/Information Technology/Information System/Data Science) with at least a CGPA of 2.5* out of 4.0 OR
  • A pass in any Diploma in Science and Technology or the equivalent with at least a CGPA of 2.75** out of 4.0.

AND

• Additional Mathematics*** —a credit in SPM or the equivalent or
• Mathematics and any 1 Science/Technology/Engineering subject —a credit in SPM or the equivalent AND pass a Mathematics placement test organised by XMUM before joining the programme.

Notes:

• Candidates with a CGPA of less than 2.5 but more than 2.0 may be accepted subject to a stringent internal evaluation process.
• Candidates with a CGPA of less than 2.75 but more than 2.5 may be accepted subject to a stringent internal evaluation process.
• The requirement for the Additional Mathematics at SPM level can be exempted if the Foundation/Matriculation or its equivalent offers a Mathematics course that is of a similar or higher level compared to the Additional Mathematics at SPM level.

Year 1:

• Calculus
• Linear Algebra
• C and C++ Programming
• Introduction to Intelligence Application
• Data Structures
• Introduction to Data Science

Year 2:

• Python and Tensorflow Programming Language
• Principles of Artificial Intelligence
• Database
• Probability Theory
• Design and Analysis of Algorithms
• Statistics
• Applied Machine Learning
• Software Engineering
• Major Elective (Choose 2):
  • Principles of Operating Systems
  • Computer Architecture
  • Computer Networks and Communication

Year 3:

• Regression Analysis
• Statistical Programming using R
• Data Mining
• Methods and Applications of Deep Learning
• Fundamental Research in Academic Project
• Time Series
• Big Data Analytics
• Major Elective (Choose 1):
  • Object-Oriented Programming-Java
  • Introduction to Cloud Computing
  • Bayesian Statistics
• Major Elective (Choose 1):
  • Natural Language Processing
  • Statistical Learning
  • Multivariate Statistical Analysis

Year 4:

• Data Science Academic Project
• Advanced Machine Learning
• Advanced Data Analysis
• Industrial Training
• Major Elective (Choose 1):
  • Deep Reinforcement Learning and Control
  • Computer Graphics