Course image AIT202 Methods and Applications of Deep Learning 2022/04 Muataz Al-Daweri
2021 - 2022

This course demonstrates the mathematic foundations of deep learning, based on which, exhaustive deep learning principles are lectured, including feed-forward neural network, regularization, optimization, convolution neural network, and sequence modeling. This is followed by deep learning application of basic methods into computer vision and natural language processing.

Lecturer: Muataz Al-Daweri

Course image AIT204 Computer Vision and Robotics 22/04 Wang Han
2021 - 2022
This course provides the students with the foundational knowledge of computer vision and robots, such as early vision methods, mid-Level methods, high-level methods and end-to-end deep learning methods.
Course image AIT205 Matrix Analysis and Application 2021/09 Sim Kuan Goh
2021 - 2022

This course introduces Matrix Analysis and Application, leveraging on the beauty and power of linear algebra and optimization. Throughout the course, students learn the principles of Matrix and apply the theories to several real-world problems in machine learning, signal processing, etc.

Lecturer Email: simkuan.goh@xmu.edu.my

Course image AIT201 Applied Machine Learning 21/09 Goh Sim Kuan
2021 - 2022

This course is to introduce the principles of various machine learning (ML) techniques. It covers topics such as the formulation of learning problems and various applications of ML. The concepts are practiced using the tools from Scikit-Learn and Tensorflow, in exercises and a project.

Lecturer Email: simkuan.goh@xmu.edu.my