ST-GIS for Engineers

Introduction to fundamental principles and concepts necessary to carry out meaningful and appropriate geographic analysis with geographic information science (GIS). Reinforcement of key issues in GIS such as geographic coordinate systems, map projections, spatial analysis, use of remotely sensed data, and visualization of spatial data. Laboratory exercises use database query, database manipulation, and spatial analysis to address problems in hydrology, water treatment, renewable energy, and transportation with an emphasis on engineering design.

GIS for Engineers

Introduction to fundamental principles and concepts necessary to carry out meaningful and appropriate geographic analysis with geographic information science (GIS). Reinforcement of key issues in GIS such as geographic coordinate systems, map projections, spatial analysis, use of remotely sensed data, and visualization of spatial data. Laboratory exercises use database query, database manipulation, and spatial analysis to address problems in hydrology, water treatment, renewable energy, and transportation with an emphasis on engineering design.

GIS for Engineers

Introduction to fundamental principles and concepts necessary to carry out meaningful and appropriate geographic analysis with geographic information science (GIS). Reinforcement of key issues in GIS such as geographic coordinate systems, map projections, spatial analysis, use of remotely sensed data, and visualization of spatial data. Laboratory exercises use database query, database manipulation, and spatial analysis to address problems in hydrology, water treatment, renewable energy, and transportation with an emphasis on engineering design.

ST-GIS for Engineers

Introduction to fundamental principles and concepts necessary to carry out meaningful and appropriate geographic analysis with geographic information science (GIS). Reinforcement of key issues in GIS such as geographic coordinate systems, map projections, spatial analysis, use of remotely sensed data, and visualization of spatial data. Laboratory exercises use database query, database manipulation, and spatial analysis to address problems in hydrology, water treatment, renewable energy, and transportation with an emphasis on engineering design.

VisualArts&HumanDevelopment II

May be taken prior to Art 510. Visual arts as they relate to the development of the individual. Presentations, workshops, current literature in the field. Topics include: grading and evaluation, discipline, special needs students, art therapy, ordering of supplies, budgets, and lesson planning. Prerequisite: Art Education major or consent of instructor.

S- Crip Theory

This course examines the interface between critical disability and sexuality studies. We will follow a genealogical approach that traces the development of crip theory in direct relation to queer theory and with particular attention to the way this field engages race and transnational political economy. As such we will explore multiple frameworks for approaching disability queerly: intersectionally, through the lens of affect, and as an assemblage signifying a temporal or spatial frame.

S-Queer Interact/MoreThanHuman

What is a "human"? And what is "nature"? How are these categories related to sexuality and queerness as well as heteronormativity? Using the tools of queer theory, critical race feminism, and settler-colonial studies, this course takes a critical approach to foundational notions of the division between human and non-human. We will consider the ways that a queer lens blurs naturalized boundaries such as those between human and non-human, nature and culture, and life and death.

ST-Predictv Mod & Uncert Quant

In this course we will discuss an array of topics that straddle probabilistic modeling and simulation, uncertainty quantification and statistical learning methods. We focus on developing systematic mathematical and computational tools for building data-driven, predictive models for complex systems and dynamics. In particular, we will discuss material that includes: uncertainty quantification, local and global sensitivity analysis methods for dynamical systems, data assimilation and approximate inference methods, stochastic optimization algorithms and model selection.
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