From July 5 to 9, 2021, students admitted in 2019 and 2020 by Kuang Yaming Honors School gathered in the Guosheng Hall for a 5-day class on mathematical modeling and machine learning. Starting from 9:00 a.m. to 10:30 a.m., the class was taught by Professor Anita Layton from the University of Waterloo via live lecturing.

On the first day, Professor Layton introduced herself and her research area, drug simulation, an emerging field that immediately intrigued her audience. The first two days were about mathematical modeling, where Professor Layton talked about predator-prey model and virus transmission model. Professor Layton spoke slowly with frequent gesturing, and there were many illustrations in the courseware, allowing students to understand more easily.

The remaining three days was about advanced machine learning. Unlike last year, Professor Layton used python for coding demonstration and talked about some common neural networks in machine learning this time. To non-AI students, neural network seemed to be high-end and esoteric, but Professor Layton made the basic principles accessible to everyone through simple and visualized examples. After the coding demonstration, students could build neural network on their own and train the model. The courses included Artificial Neural Network, Convolutional Neural Network, Recurrent Neural Network and Generative Adversarial Network. Those concepts were rather new to the students, and most of them found it difficult to understand coding. Nevertheless, they still paid full attention and worked hard after class.

During the class, the students learned two important mathematical models and the fundamentals of neural networks, which should have laid a solid foundation for their future study and research.