51 - 60 of 228 results for: MS

Human decision making is increasingly being displaced by predictive algorithms. Judges sentence defendants based on statistical risk scores; regulators take enforcement actions based on predicted violations; advertisers target materials based on demographic attributes; and employers evaluate applicants and employees based on machine-learned models. One concern with the rise of such algorithmic decision making is that it may replicate or exacerbate human bias. This course surveys the legal and ethical principles for assessing the equity of algorithms, describes statistical techniques for designing fair systems, and considers how anti-discrimination law and the design of algorithms may need to evolve to account for machine bias. Concepts will be developed in part through guided in-class coding exercises. Admission is by consent of instructor and is limited to 20 students. CONSENT APPLICATION: To enroll in the class, please complete the course application by March 15, 2021 available at: https://5harad.com/mse330/. Elements used in grading: Grading is based on response papers, class participation, and a final project. Cross-listed with Comparative Studies in Race & Ethnicity ( CSRE 230), Management Science & Engineering (MS&E 330), Sociology ( SOC 279).

The course follows the patent application process through the important stages: inventor interviews, patentability analysis, drafting claims, drafting a specification, filing a patent application, and responding to an office action. The subject matter and practical instruction relevant to each stage are addressed in the context of current rules and case law. The course includes four written assignments: an invention capture, a claim set, a full patent application, and an Office Action response. Pre-requisites: Law 326 (IP:Patents), Law 409 (Intro IP), ME 208, or MS&E 278.

The Leadership Lab (previously known as d.Leadership) is a one-of-a-kind hands-on leadership course. This course bridges leadership research and principles with real-world application, offering a unique opportunity to grasp not only the theory but also the practical application of leadership. Real Application: Embrace a dynamic learning environment where theory meets practice. You will apply a wide range of leadership capabilities and skills within real, live teams and environments - all with instruction along the way. Experiment with your Leadership Style: We believe your leadership style is something you must prototype and iterate throughout your life. This course creates a safe environment where you can practice new leadership techniques without worrying about your reputation or next performance review in a real work environment. As you practice new techniques, you will undoubtedly experience highs and lows and most importantly refine your own leadership point of view. Key Topic Areas: Leveraging Failure and Learning to Pivot; Leading with Influence in the Absence of Authority; Framing Projects with Purpose in Order to Drive Momentum; and Subtracting Friction in Organizational Change. By the end of this course, you will have enhanced and transformed your leadership capabilities, found your natural strengths, enhanced them, and explored new horizons. Join us and experience a leadership journey that is both inspiring and hands-on. Preference to graduate students and students who have previously taken MS&E 280 or equivalent (not a prerequisite). Reach out to the teaching team with questions. Admission by Application https://forms.gle/B4sFZxjTaN4fFvRQ9 due 5pm on March 22, 2024.

Directed research experience for MS students in mechanical engineering who are pursuing the Distinction in Research (DiR). The student is responsible for securing a faculty research advisor and will register under that advisor's section number. Students must provide confirmation of faculty research advisor's agreement to supervise DiR, at which time they will receive a permission code from ME Student Services allowing them to enroll. Course may be repeated for credit.

Fundamental concepts and tools for the analysis of problems under uncertainty, focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, belief networks, random variables, conditioning, and expectation. The course is fast-paced, but it has no prerequisites.

With the recent developments in generative AI, the value in human creativity is increasingly a focus. Course draws from lessons from creativity in the arts to teach engineering students methods for creativity derived from musicians and artists. For our engineering students to learn creativity as a skill that is distinguishable and differentiated from generative artificial intelligence, this course explores, for instance the anatomy of a Hollywood pop song and the process behind the creation of globally impactful art. Students learn how to transfer these skills into the creation of engaging entrepreneurial solutions, for effective storytelling, and in developing their unique personal and professional stories. Students learn skills to unlock creative power which they will apply in the course as a design vehicle for a wide range of applications in engineering, self-expression, technological exploration, and the development of solutions that are centered around human connection and emotional engagement with the user. Sessions are practical, drawing tools and lessons from interdisciplinary individuals with wide-ranging careers. No artistic or entrepreneurial experience necessary.