Course Description: Applies engineering science, design methods, and system analysis to developing areas and current problems in chemical engineering. Topics are announced at registration.

Course Description: Special Topics in CHE

Course Description: Chemical Engineering special topics vary by section.

Course Description: Project-driven course focusing on biomedical product design with emphasis on marketability, innovation, entrepreneurship and business. Topics include design fundamentals, problem/needs identification, delineation of realistic constraints and product specifications, intellectual property, market analysis, entrepreneurship, specific advanced design, business plan development, venture funding, and medical product testing methods. Pre-requisite: BME 2000 or instructor permission.

Course Description: A project-based grounding in biomedical product design, with emphasis on clinical immersion and topics including design fundamentals, problem/needs identification, delineation of realistic constraints and product specifications, intellectual property, market analysis, entrepreneurship, specific advanced design topics, business plan development, venture funding, and medical product testing methods. Prerequisite: Instructor Permission

Course Description: This course introduces techniques for constructing mathematical and computational models of biological processes and utilizing experimental data to validate those models at many levels of organizational scale -- from genome to whole-tissue. Prerequisites: APMA 2130 or MATH 3250 or APMA 2501 - Differential Equations & Linear Algebra, and APMA 3110 or APMA 3100 or MATH 3100, and BME 2101, and BME 2104, and BME 2315 and BME major or minors

Course Description: Introduces techniques for constructing mathematical and computational models of biological processes at many levels of organizational scale from genome to whole-tissue. Topics include choice of techniques, quantitative characterization of biological properties, assumptions and model simplification, parameter estimation and sensitivity analysis, model verification and validation and integration of computational modeling w/experimental approaches.Prerequisites: BME 6101, and BME 2104 or BME 7806 (or equivalent).

Course Description: A lab-based course that provides a hands-on way to learn about new developments in electrical and computer engineering fields. Topics include technologies or application areas that relate to ongoing design and research activities of faculty and students.

Course Description: Student-led special topic courses which vary by semester

Course Description: Student led special topic courses which vary by semester.

Course Description: A rich body of literature has emerged about the design, implementation, and analysis of experiments in field settings. This course introduces students to advances in the design and analysis of field experiments; provides opportunities for students to read and discuss well-known field experiments that have had important implications for policy; and discusses methodological issues related to both experiments and non-experiments.

Course Description: Overview of the mechanical engineer's role as analyst and designer. Introduction to manufacturing tools, equipment, and processes; properties of materials relative to manufacture and design. Pre-requisite: PHYS 1425 or PHYS 1420 or PHYS 1710. Co-requisite: APMA 2120 or MATH 2310 or MATH 2315

Course Description: Historical introduction, standard atmosphere, basic aerodynamics, airfoils and wings, flight mechanics, stability and control, propulsion (airbreathing, rocket and space), orbital mechanics.

Course Description: Special topics in graduate engineering will vary based upon student and faculty interests.

Course Description: Covers data pipeline: techniques to collect data, organize, query & apply the data, and generate products that describe the insights. Topics include Python environments, containers using Docker, data wrangling with pandas, data acquisition via flat files, APIs, JSON formats, and webscraping, relational, document, and graph databases, exploratory data analysis including static & interactive data visualization, dashboards, and cloud computing.