Fundamentals of graphical communication within the context of engineering and technical design. Topics include sketching, line drawing, and solid modeling. Development and interpretation of drawings and specifications for product realization is emphasized.

Probability theory, statistical inference, and data analysis with a focus on applications relevant to engineering practice. Topics include probability distributions, including discrete and continuous distributions such as binomial, normal, and exponential distributions, statistical inference, estimation, hypothesis testing, and regression analysis.

Challenges, emerging trends, and advancements shaping the field of engineering in the 21st century. Engineering ethics, communications for engineers, sustainability, and professionalism will be covered through case studies and guest lectures from industry representatives.

Theory, techniques, and applications of artificial intelligence and machine learning within the field of engineering. Case studies will explore how AI technologies are leveraged to enhance problem-solving, decision-making, and innovation across various engineering domains.

Supervised practical experience related to the Engineering field in an elected setting planned in conjunction with the relevant Engineering faculty. Pass/Fail credit.

Selected topics in engineering. Topics vary depending on faculty expertise. This course may be repeated for credit if the topic is different.

A planned individual research experience carried out in conjunction with an engineering faculty member. Course may be repeated for a total of no more than three hours of undergraduate credit.