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...the university of choice for accomplished, high-performing...1,651 Engineering: 11,534 Humanities and Social...
Electrical Engineering (BS): Power Systems Concentration
...courses provide a foundation for all EE students...513, ECE 533, ECE 534, ECE 550, ECE...
FOR 534 Forest Operations and Analysis
Management science and operational techniques in forestry. Logging road layout and construction, and machine systems: harvesting machine optimization and selection. Harvesting, production and forest planning. Decision and inventory theory, and other techniques for solving problems typically encountered in forest operations management. Required overnight weekend field trip.
Junior standing or above
Typically offered in Spring only
EM 534 Artificial Intelligence for Engineering Managers
This course is designed for engineering managers to develop the skills necessary to manage AI and machine learning projects. It covers a broad range of AI topics including the various methods and algorithms (such as machine learning, deep learning, and large language models) and associated applications in different industries. The focus is on understanding the technical aspects of AI sufficient to manage teams, make informed decisions on AI adoption, and create project plans that estimate resources, costs, and timelines. The course aims to equip managers with the knowledge to assess the impact of AI on their firms and the broader economy. It is not a technical course for becoming an AI/ML engineer, but rather a management-oriented course to help in the deployment and oversight of AI projects.
Typically offered in Fall, Spring, and Summer
ISE 534 Artificial Intelligence for Engineering Managers
This course is designed for engineering managers to develop the skills necessary to manage AI and machine learning projects. It covers a broad range of AI topics including the various methods and algorithms (such as machine learning, deep learning, and large language models) and associated applications in different industries. The focus is on understanding the technical aspects of AI sufficient to manage teams, make informed decisions on AI adoption, and create project plans that estimate resources, costs, and timelines. The course aims to equip managers with the knowledge to assess the impact of AI on their firms and the broader economy. It is not a technical course for becoming an AI/ML engineer, but rather a management-oriented course to help in the deployment and oversight of AI projects.
Typically offered in Fall, Spring, and Summer