5. 1.5 Lecture Hour. Advanced topics in machine learning for data science in energy systems; topics include supervised and unsupervised learning, clustering, classification, advanced predictive models, advanced performance evaluation, neural networks and reinforcement learning. Prerequisites: Graduate classification; ENGY majors; ENGY 640 and ENGY 641, or approval of instructor Credit 1.
5. 1.5 Lecture Hour. Advanced topics in machine learning for data science in energy systems; topics include supervised and unsupervised learning, clustering, classification, advanced predictive models, advanced performance evaluation, neural networks and reinforcement learning. Prerequisites: Graduate classification; ENGY majors; ENGY 640 and ENGY 641, or approval of instructor Credit 1.
