Course Description: Instructional design and development of online courses within formal educational settings (for-credit higher education courses, virtual k-12 schools, professional credentialing) with regular and substantive interaction in a learning community. Develop assessments and weekly units of instruction inside of a learning management system. Online teaching in both asynchronous and synchronous settings. Discussion of current topics in distance education.

Course Description: Analyzes modern engineering optics and methods; fundamentals of coherence, diffraction interference, polarization, and lasing processes; fluid mechanics, heat transfer, stress/strain, vibrations, and manufacturing applications; laboratory practice: interferometry, schlieren/shadowgraph, and laser velocimetry. Prerequisite: PHYS 2415.

Course Description: Required one-hour weekly seminar for doctoral students in mechanical, aerospace, and nuclear engineering. Students enrolled in MAE 9999 may make formal presentations of their work.

Course Description: Technology class introducing students to the fundamental applications of geographic information systems central to planning analysis and practice.

Course Description: Trends in hardware and software for Big Data Systems and applications. Cover principles driving data infrastructures, which enabled the training of AI models on datasets (speech, sounds, images, video, languages) and may extend to structured data (text, images, time series). AI and machine learning practitioners build and deploy data science projects on Amazon Web Services unifying data science, data engineering, and application development.

Course Description: "We will explore engineering methods to use ""microbes as tools"" for human wellbeing, to understand and combat ""microbes as enemies"" in infectious disease, and to characterize and manipulate ""microbes as partners"" in human health and wellbeing. We will learn how facets of BME are used to test hypotheses of human/microbe relationships and to design strategies to understand and treat disease and improve human wellbeing. Prerequisites: BME 2000 AND (BME 2101 OR BME 2102) AND BME 2104 AND BME 2315"

Course Description: Students learn foundational principals of advanced research, including hypothesis formulation, experimental design, and statistical methods to assess experimental data as it relates to hypothesis testing. Prerequisites: Previous exposure to statistics and programming in a language such as Python, MATLAB, or R.

Course Description: A year-long research project in biomedical engineering conducted in consultation with a department faculty advisor; usually related to ongoing faculty research. Includes the design, execution, and analysis of experimental laboratory work and computational or theoretical computer analysis of a problem. Requires a comprehensive report of the results. Prerequisite: third- or fourth-year standing, and instructor permission.

Course Description: Applies engineering science, design methods, and system analysis to developing areas and current problems in biomedical engineering. Topics vary by semester.

Course Description: Under faculty supervision, students plan a project of at least one semester's duration, conduct the analysis or design and test, and report on the results. If this work is to be the basis for an undergraduate thesis, the course should be taken no later than the seventh semester. Prerequisite: Instructor permission.

Course Description: Under faculty supervision, students plan a project of at least one semester's duration, conduct the analysis or design and test, and report on the results. If this work is to be the basis for an undergraduate thesis, the course should be taken no later than the seventh semester. Prerequisite: Instructor permission.

Course Description: Integration of computer organization concepts such as data flow, instruction interpretation, memory systems, interfacing, and microprogramming with practical and systematic digital design methods such as behavioral versus structural descriptions, divide-and-conquer, hierarchical conceptual levels, trade-offs, iteration, and postponement of detail.  Design exercises are accomplished using a hardware description language and simulation.  Prerequisite by topic:  Digital Logic Design (ECE 2330 or equivalent), Introductory Computer Architecture (ECE 3330 or equivalent), Assembly Language Programming.

Course Description: Special Topics in Engineering.

Course Description: Advance projects course to be taken in parallel with STS 4010, 4020, or can be used for an advanced undergraduate course on a topic not covered in the course offerings. Prerequisite: instructor permission.

Course Description: Applies common frameworks and methodologies to the examination of enterprise system architecture needs. Includes coverage of the systems development life cycle and the methodologies in use characterized by their varying degrees of iteration, structure, and user involvement. Emphasizes analytical and design concepts and related tools such as use cases and Unified Modeling Language.