Below are the key courses that I teach at PSU. For more information, click on the course link:

Machine Learning: This is an introductory course to ML. The course will teach students the mathematical foundations and programming skills to develop, train, and test ML models. Some of the models we will cover include: linear regression, logistic regression, neural networks, support vector machines, and clustering, among others. Concepts include maximum likelihood estmation, bias-variance tradeoff, sparsity, model selection, and cross validation, among others.

Virtual Reality: This is an introductory course to VR. The course covers various topics ranging from hardware and software requirements for VR to neuroscience and human brain operation as they relate to VR. The course also has a project component and students who are interested could develop VR/AR applications and present a demo of their application to the entire class.

Wireless Networks and Applications: This is an introductory course to mobile and wireless networks with emphasis on fundamentals of wireless communication, MAC/PHY/networking, wireless security and wireless applications in smart cities, connected vehicles, and healthcare. The course promarily focuses on WiFi (both low and high frequency) but it also brings in topics from cellular communication.