HKU Moodle

This course aims to provide students with an in-depth introduction to the Internet-of-Things (IoT) and its applications to Industrial Engineering. It will cover some basic concepts and technologies such as IoT network architecture, sensors and devices, IoT communication techniques, wireless sensor networks, edge computing, embedded systems, cloud computing, data analytics, distributed computing, control, etc. The applications of IoTs will also be discussed

This course aims to provide students with an in-depth introduction to Machine Learning and its application to Industrial Engineering. It will cover some basic concepts such as supervised and unsupervised learning, model training, testing, and validation, as well as the main models and algorithms for classification and regression. Topics such as linear and logistic regression, regularization, probabilistic inference, support vector machines, kernel methods, dimensionality reduction, feedforward neural networks, convolutional neural networks, recurrent neural networks will be discussed in detail

This course provides a comprehensive introduction to computer vision, covering traditional topics such as image formation, image processing, model fitting and optimization, and recognition. It places significant emphasis on deep generative models, a central technique in Generative AI, including Variational Autoencoders, Generative Adversarial Networks, Transformers, Normalizing Flows, Diffusion Models, and Flow-Matching. Additionally, the course explores advanced computer vision applications, such as motion estimation, SLAM (Simultaneous Localization and Mapping), 3D reconstruction, and image-based rendering, which have widespread applications in robotics and automation.