The UVM College of Engineering and Mathematical Science offers over 100 active and project-based learning courses that engage students in hands-on and applied problem-solving throughout the curriculum. In field courses, students learn to use state-of-the art equipment and standard protocols. In service-learning courses, students apply their learning to help solve a problem or need identified by a community partner.
Professional ethics
Students in CEMS will become the innovators of tomorrow’s technology and thus should understand the potential implications of their work on the well-being of people, society and the planet. Professional Ethics courses provide students the opportunity to consider the ethical implications of their academic discipline, including the social costs and benefits, environmental justice, and historical perspectives including, but not limited to, associated social, economic, environmental, and geopolitical issues.
Communication intensive
In these courses, students develop their ability to effectively communicate technical knowledge in written and oral forms to a wide range of audiences. Students complete at least one course covering basic principles of technical writing and effective oral communication and later apply these skills in more advanced courses in their discipline.
Teamwork and leadership
In these courses, students develop the ability to function effectively in a team and to create a collaborative and inclusive work environment with others. Students develop leadership skills that enable them to (1) establish and work toward common goals, plan tasks, and meet objectives, (2) identify constructive and destructive group behaviors, and (3) mediate conflict.
Data dexterity
In these courses, CEMS students gain significant experience processing and analyzing data and drawing meaningful conclusions from them. Students also develop an appreciation for the uncertainty and variability in data measurements and forecasting across applications. Data Dexterity courses provide students the opportunity to (1) explore data analysis and synthesis through a variety of statistical and optimization tools and data visualization, (2) practice proper data handling techniques, and (3) discern how these skills can be used to address real-world problems in their field of study.