This course introduces students to the underlying building blocks of digital system and microcontroller design. Digital systems topics that are covered include: number systems, truth tables, Boolean algebra, combinational and sequential logic, and finite state machines. A microcontroller is used to teach register programming, reading and writing digital I/O, bitwise operations and bit-masking and microprocessor architecture. Laboratory exercises are designed to illustrate concepts, reinforce analysis and design skills, and develop instrumentation techniques associated with the lecture topics.

Machine learning has applications in a wide variety of fields ranging from medicine and finance to telecommunications and autonomous self-driving vehicles. This course introduces machine learning and gives you the knowledge to understand and apply machine learning to solve problems in a variety of application areas. The course covers neural net structures, deep learning, support vector machines, training and testing methods, clustering, classification, and prediction with applications across a variety of fields. The focus will be on developing a foundation from which a variety of machine learning methods can be applied. Students may not take and receive credit for this course if they have already taken EEET-520.