COMSC 415: Machine Learning taught by Professor Sonya Cates, teaches students how to build computer systems that learn from data to make predictions, recognize patterns and organize information. Students are introduced to supervised and unsupervised machine learning, identify classification problems and are trained to use the tools and techniques that are implemented in the industry. It's important for students today to learn how to make these data-driven computer systems because they're used for much more than allowing your face to unlock your phone. They protect us against credit card fraud and spam emails. They allow Amazon Alexa to speak to us and are one of the key components in building self-driving cars. Have you ever wondered how your cell phone unlocks just by using your face? How is it able to detect the difference between your face and someone else’s? This feature, now prominent in most cell phones, is just one type of machine learning that RWU students are learning how to build. In a computer science course, students went behind the screen to learn how facial recognition computer systems are constructed and how this type of technology can be applied to future devices. “Instead of writing a program to recognize faces by defining what eyes are, what a nose is, you can show a computer a lot of pictures of faces and have it learn what a face is by itself,” Cates said. “What I teach are very basic techniques but they are related to what would be going on behind the scenes in something like a self-driving car or any other automated technology that uses images.”