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161 - 170 of 353 results for: CSI::certificate

EE 292H: Engineering, Entrepreneurship & Climate Change

The purpose of this seminar series course is to help students and professionals develop the tools to apply the engineering and entrepreneurial mindset to problems that stem from climate change, in order to consider and evaluate possible stabilizing, remedial and adaptive approaches. This course is not a crash course on climate change or policy. Instead we will focus on learning about and discussing the climate problems that seem most tractable to these approaches. Each week Dr. Field and/or a guest speaker will lead a short warm-up discussion/activity and then deliver a talk in his/her area of expertise. We will wrap up with small-group and full-class discussions of related challenges/opportunities and possible engineering-oriented solutions. Class members are asked to do background reading before each class, to submit a question before each lecture, and to do in-class brainstorming. May be repeated for credit.
Terms: Aut | Units: 1 | Repeatable for credit
Instructors: Field, L. (PI)

EE 292T: SmartGrids and Advanced Power Systems Seminar (CEE 272T)

A series of seminar and lectures focused on power engineering. Renowned researchers from universities and national labs will deliver bi-weekly seminars on the state of the art of power system engineering. Seminar topics may include: power system analysis and simulation, control and stability, new market mechanisms, computation challenges and solutions, detection and estimation, and the role of communications in the grid. The instructors will cover relevant background materials in the in-between weeks. The seminars are planned to continue throughout the next academic year, so the course may be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-2 | Repeatable for credit

EE 293B: Fundamentals of Energy Processes (ENERGY 293B)

For seniors and graduate students. Covers scientific and engineering fundamentals of renewable energy processes involving heat. Thermodynamics, heat engines, solar thermal, geothermal, biomass. Recommended: MATH 19-21; PHYSICS 41, 43, 45
Terms: Win | Units: 3

EMED 255: Design for Health: Helping Patients Navigate the System (DESINST 255)

For many people, participating in the American healthcare system is confusing, frustrating and often disempowering. It is also an experience fueled with emotional intensity and feelings of vulnerability. The current ecosystem, with its complexity and multiple stakeholders, is rife with human-centered design opportunities. An especially sticky set of issues lies in the ways people navigate healthcare: understanding how the system works, accessing information about services, making decisions about treatment and interventions, and advocating for needs.nAdmission by application. See dschool.stanford.edu/classes for more information.
Terms: Aut | Units: 2

ENERGY 101: Energy and the Environment (EARTHSYS 101)

Energy use in modern society and the consequences of current and future energy use patterns. Case studies illustrate resource estimation, engineering analysis of energy systems, and options for managing carbon emissions. Focus is on energy definitions, use patterns, resource estimation, pollution. Recommended: MATH 21 or 42.
Terms: Win | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA

ENERGY 101A: Energizing California

A weekend field trip featuring renewable and nonrenewable energy installations in Northern California. Tour geothermal, bioenergy, and natural gas field sites with expert guides from the Department of Energy Resources Engineering. Requirements: One campus meeting and weekend field trip. Enrollment limited to 25. Freshman have first choice.
Terms: Spr | Units: 1
Instructors: Onori, S. (PI)

ENERGY 102: Fundamentals of Renewable Power (EARTHSYS 102)

Do you want a much better understanding of renewable power technologies? Did you know that wind and solar are the fastest growing forms of electricity generation? Are you interested in hearing about the most recent, and future, designs for green power? Do you want to understand what limits power extraction from renewable resources and how current designs could be improved? This course dives deep into these and related issues for wind, solar, biomass, geothermal, tidal and wave power technologies. We welcome all student, from non-majors to MBAs and grad students. If you are potentially interested in an energy or environmental related major, this course is particularly useful. Recommended: Math 21 or 42.
Terms: Spr | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-SMA

ENERGY 104: Sustainable Energy for 9 Billion

This course explores the transition to a sustainable energy system at large scales (national and global), and over long time periods (decades). Explores the drivers of global energy demand and the fundamentals of technologies that can meet this demand sustainably. Focuses on constraints affecting large-scale deployment of technologies, as well as inertial factors affecting this transition. Problems will involve modeling global energy demand, deployment rates for sustainable technologies, technological learning and economics of technical change. Recommended: ENERGY 101, 102.
Terms: Spr | Units: 3 | UG Reqs: WAY-AQR

ENERGY 110: Engineering Economics

The success of energy projects and companies is judged by technical, economic and financial criteria. This course will introduce concepts of engineering economy, e.g., time value of money, life cycle costs and financial metrics, and explore their application to the business of energy. We will use case studies, business school cases and possibly industry guest lecturers. Examples from the hydrocarbon businesses that dominate energy today will provide the framework for the analysis of both conventional and renewable energy.
Terms: Spr | Units: 3

ENERGY 160: Uncertainty Quantification in Data-Centric Simulations (ENERGY 260)

This course provides a brief survey of mathematical methods for uncertainty quantification. It highlights various issues, techniques and practical tools available for modeling uncertainty in quantitative models of complex dynamic systems. Specific topics include basic concepts in probability and statistics, spatial statistics (geostatistics and machine learning), Monte Carlo simulations, global and local sensitivity analyses, surrogate models, and computational alternatives to Monte Carlo simulations (e.g., quasi-MC, moment equations, the method of distributions, polynomial chaos expansions). Prerequisites: algebra ( CME 104 or equivalent), introductory statistics course ( CME 106 or equivalent).
Terms: Win | Units: 3
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