In addition to the project work, we will bring in local experts to discuss a number of relevant topics with the class these are shown in the syllabus, below. There will be two class meetings per week, each of three hours duration. The set of projects might include investigations suggested by industry partners. Required activities will include a written project proposal of work to be undertaken, informal group-generated oral presentations on technical issues, periodic formal written progress reports, a final project oral presentation, and a final project paper. In this two-semester course students will engage in the collaborative design and execution of a year-long Instrumentation and measurement-intensive technical project. PHYS 523 Instrumentation and Applied Physics Project credit: 4 Hours. Other students may enroll with permission of the M.Eng. Primarily for students in the Engineering: Instrumentation and Applied Physics, MEng program. Prerequisite: Familiarity with a high-level computing language such as C++, Python, or Java mathematical competence typical of graduates (either as majors or minors) from undergraduate programs in Physics and Astronomy. Through these projects and the course material, students will learn how large datasets in physics are generated, curated, and analyzed, using machine learning as a tool to generate key insights in both experimental and theoretical science. Example projects might include machine learning approaches to searches for new particles or interactions at high-energy colliders methods of particle tracking and reconstruction identification, classification and measurement of astrophysical phenomena novel approaches to medical imaging and simulation using techniques from physics and machine learning machine learning in quantum information science. Research-inspired projects are an important part of the course and students will not only execute them but will play an active role in helping define and shape them. The course uses open scientific data, open source software from data science and physics-related fields, and publicly-available information as enabling elements. A distinguishing feature of this course is its sharp focus on endeavors in the data-rich physical sciences as the arenas in which modern machine learning techniques are taught. The lists of suggested readings and references are advisory a large amount of material of excellent quality is now available on the worldwide web, particularly on the sites of university courses addressing the topics of each unit. Material will be clustered into units of varying duration, as indicated below. The list of topics will evolve, according to the interests of the class and instructors. There will be a few projects throughout semester that will build on the course material and utilize open source software and open data in physics and related fields. There will be two 75-minute classes each week, split into discussions of core principles and hands-on exercises involving coding and data. This course will introduce students to the fundamentals of analysis and interpretation of scientific data, and applications of machine learning to problems common in laboratory science such as classification and regression. PHYS 503 Instrumentation Physics Applications of Machine Learning credit: 4 Hours.ĭesigned to give students a solid foundation in machine learning applications to physics, positioning itself at the intersection of machine learning and data-intensive science. Prerequisite: Instructor Approval Required. The event will be specific to each offering and may include activities such as physics-based museum exhibits and performance pieces. The projects will be presented at a culminating event at the end of the semester. This process will include: Project design independent study team work and dedicated assignments. With collaboration and guidance from their instructors and across-campus experts, student projects will be taken from inception to completion. Identifying themes based on their exposure and interest, students will form interdisciplinary project teams. Students will explore the stunning creations that have emerged from synergies between the sciences and the arts. Students will explore such physics topics while they actively participate in a broad range of artistic practices and expression. Where Art Meets Physics is a project-based, cross-disciplinary course for students interested in both exposure to the frontiers of physics and experiences in the arts. PHYS 495 Where the Arts Meets Physics credit: 3 Hours.
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