| This course builds solely on basic programming skills to introduce the field of deep learning, neural network architectures, and learning algorithms in a way accessible to cadets pursuing a variety of majors. Cadets will develop an understanding of emerging trends and research in the field. Major emphasis is placed on applying neural networks to problems in a variety of domains by training and tuning models for tasks such as pattern recognition, time series prediction, data mining, and optimization. Hands-on exercises, programming assignments, and case studies will provide cadets with valuable experience using state-of-the-art software libraries and pre-trained models (PTMs). The course culminates in an open-ended project of the cadets' choosing but intended to be an application of course content to cadets' personal research projects. *This is a pilot course and must be reviewed by the Curriculum Committee NLT AY25 to continue. ET credit pending ABET-PEV review." |