Offered: Spring 2024, 2023, 2022, 2021, 2020, 2019
Course Description: Consideration of the human (e.g., operator, user, maintainer) is a critical component to systems engineering. The goal of Human Systems Integration (HSI) is to account for human capabilities and limitations when designing and evaluating complex systems, in order to enhance safety, performance, usability, sustainability, and reduce life cycle costs. This course will cover research methods and design issues relevant to HSI across various contexts, such as transportation, healthcare, manufacturing, defense, and other complex control systems. Students will gain practical knowledge of how to integrate human factors into the design and evaluation of complex systems.
Note: Previously listed as ENGR 581a4: Human Systems Integration
Offered: Fall 2024; Summer 2023; Fall 2022, 2021, 2020, 2019
Course Description: Data processing and visualization is increasingly important in today’s data driven world, where proper management of data can facilitate the integration and evaluation of systems and projects. The goal of this class is to provide engineers with practical and applicable data science skills, including data aggregation and filtering, intuitive data exploration, effective communication of patterns, summaries, and findings, and methods of archiving for data sharing or future use. This class combines principles and theories of information visualization and data management with implementation techniques centered around the R statistical software program. Previous experience with R is not required, but a basic working knowledge of, or willingness to learn, will help students in this class.
Note: Previously listed as ENGR 580a5: Systems Data Lifecycle and Visualization
Offered: Spring 2023; Fall 2020; Summer 2019
Course Description: Engineering risks are inherent in the design, development, and operation of complex systems. Risk analysis is a critical process for identifying and mitigating potential hazards that can threaten the safety, health, and success of individuals, organizations, and the environment. Through a combination of lectures, case studies, and hands-on exercises, this course will provide you with the tools and techniques needed to make better risk decisions based on quantitative risk analyses and modeling, hazard analysis, fault tree analysis, decision diagramming, and risk management and planning.
Offered: Spring 2024, 2022
Course Description: Engineers are encountering and generating an ever-growing body of data in their work. Extracting knowledge and insights from that data, with understandable uncertainty, requires the application of data science techniques. These approaches are increasingly focused on computer based statistical computations but require foundational knowledge to deliver valid and interpretable results. This course is designed to provide students with: (1) A working knowledge of the statistics required for engineering analytics; (2) Introduction to, and practice with, the tools required for data mining and analytics in professional engineering settings; and (3) Applications to real-world engineering examples.
Note: Previously listed as ENGR 380a4: Engineering Data Analytics