Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular …
An introduction to the analysis, design and evaluation of human-centered systems. User interaction can be designed to leverage the strengths of people in controlling automation and analyzing data. Topics include …
Introduces modeling, analysis, and control of dynamic systems, using ordinary differential and difference equations. Emphasizes the properties of mathematical representations of systems, the methods used to analyze mathematical models, and …
Data mining describes approaches to turning data into information. Rather than the more typical deductive strategy of building models using known principles, data mining uses inductive approaches to discover the …
This course shows how to use linear statistical models for analysis in engineering and science. The course emphasizes the use of regression models for description, prediction, and control in a …
A case-based approach to the design of user interfaces with a focus on iterative project experiences. Display design concepts are related to ecological factors, situational awareness, attention, vision, and information …
A first graduate course covering the theory and practice of discrete-event stochastic simulation. Coverage includes Monte Carlo methods and spreadsheet applications, generating random numbers and variates, specifying input probability distributions, …
The goals of this course are to educate graduate students in SEAS in the ethical conduct of research & publication, and to facilitate the thoughtful integration of ethics into their …
This course provides an introduction to network and combinatorial optimization at the level of a second graduate course in optimization. Designed to complement SYS 6003, but the course is not …
Presents the foundations of mathematical modeling and optimization, with emphasis on problem formulation and solution techniques. Includes applications of linear programs, nonlinear programs, and combinatorial models, as well as a …