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91 - 100 of 201 results for: all courses

EE 114: Fundamentals of Analog Integrated Circuit Design (EE 214A)

Analysis and simulation of elementary transistor stages, current mirrors, supply- and temperature-independent bias, and reference circuits. Overview of integrated circuit technologies, circuit components, component variations and practical design paradigms. Differential circuits, frequency response, and feedback will also be covered. Performance evaluation using computer-aided design tools. Undergraduates must take EE 114 for 4 units. Prerequisite: 101B. GER:DB-EngrAppSci
Terms: Aut | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA

EE 115: Taking the Pulse of the Planet (GEOPHYS 115)

Grappling with the big questions of sustainability and climate change, requires that we have ways to measure ? as we cannot manage what we cannot measure. This course, Taking the Pulse of the Planet introduces a new research and teaching initiative at Stanford ? also called Taking the Pulse of the Planet, which has the following goal: to have in place a global network of satellite, airborne, land/water-based sensors to support the real-time adaptive management of planetary health and human activities. Measurements will be made at the spatial and temporal scales required to inform the development and implementation of new policies addressing critical issues related to climate change, sustainability, and equity. Tapping into rapid advancements in sensor technology and data science over the past decade, we can now image and monitor many components of the Earth system and human activities. With the launch of the Stanford Doerr School of Sustainability, we wish to celebrate, through this co more »
Grappling with the big questions of sustainability and climate change, requires that we have ways to measure ? as we cannot manage what we cannot measure. This course, Taking the Pulse of the Planet introduces a new research and teaching initiative at Stanford ? also called Taking the Pulse of the Planet, which has the following goal: to have in place a global network of satellite, airborne, land/water-based sensors to support the real-time adaptive management of planetary health and human activities. Measurements will be made at the spatial and temporal scales required to inform the development and implementation of new policies addressing critical issues related to climate change, sustainability, and equity. Tapping into rapid advancements in sensor technology and data science over the past decade, we can now image and monitor many components of the Earth system and human activities. With the launch of the Stanford Doerr School of Sustainability, we wish to celebrate, through this course, the powerful role that advancements in technology ? specifically sensors ? and advancements in data science are playing in addressing the global challenges in sustainability and climate change. This will be a lecture class for undergraduates and graduate students designed to introduce them to the incredible array of sensors and data sets now available. We will finish the quarter with group projects that will involve the making and deployment of sensors around campus. The course will be designed to accommodate students at any level, with any background, with no required pre-requisites. In most of the assignments, we will be using Google co-lab to work with various types of sensor data. We anticipate drawing to this course both data-science-savvy and data-science-interested students. Therefore, we have developed online modules that are designed to help any student get up to speed on the "jargon" and the computational approaches used in the class.
| UG Reqs: WAY-AQR, WAY-SMA

EE 134: Introduction to Photonics

Optics and photonics underpin the technologies that define our daily life, from communications and sensing to displays and imaging. This course provides an introduction to the principles that govern the generation, manipulation, and detection of light and will give students hands-on lab experience applying these principles to analyze and design working optical systems. The concepts we will cover form the basis for many systems in biology, optoelectronics, and telecommunications and build a foundation for further learning in photonics and optoelectronics. Connecting theory to observation and application is a major theme for the course. Prerequisite: EE 102A and one of the following: EE 42, Physics 43, or Physics 63.
Terms: Win | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA

EE 178: Probabilistic Systems Analysis

Introduction to probability and its role in modeling and analyzing real world phenomena and systems, including topics in statistics, machine learning, and statistical signal processing. Elements of probability, conditional probability, Bayes rule, independence. Discrete and continuous random variables. Signal detection. Functions of random variables. Expectation; mean, variance and covariance, linear MSE estimation. Conditional expectation; iterated expectation, MSE estimation, quantization and clustering. Parameter estimation. Classification. Sample averages. Inequalities and limit theorems. Confidence intervals. Prerequisites: Calculus at the level of MATH 51, CME 100 or equivalent and basic knowledge of computing at the level of CS106A.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

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.
Terms: Win | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA

ENERGY 104: Sustainable Energy for 9 Billion (ENERGY 204)

This course explores the global transition to a sustainable global energy system. We will formulate and program simple models for future energy system pathways. We will explore the drivers of global energy demand and carbon emissions, as well as the technologies that can help us meet this demand sustainably. We will consider constraints on the large-scale deployment of technology and difficulties of a transition at large scales and over long time periods. Assignments will focus on building models of key aspects of the energy transition, including global, regional and sectoral energy demand and emissions as well as economics of change. Prerequisites: students should be comfortable with calculus and linear algebra (e.g. Math 20, Math 51) and be familiar with computer programming (e.g. CS106A, CS106B). We will use the Python programming language to build our models.
Terms: Win | Units: 3 | UG Reqs: WAY-AQR

ENGLISH 184E: Literary Text Mining

This course will train students in applied methods for computationally analyzing texts for humanities research. The skills students will gain will include basic programming for textual analysis, applied statistical evaluation of results and the ability to present these results within a formal research paper or presentation. Students in the course will also learn the prerequisite steps of such an analysis including corpus selection and cleaning, metadata collection, and selecting and creating an appropriate visualization for the results. This class is enrollment by permission only. To request a spot in the class, please fill out the survey: https://stanforduniversity.qualtrics.com/jfe/form/SV_6PrXGyFeo7g5eNU
Terms: Aut | Units: 5 | UG Reqs: GER:DB-Hum, WAY-AQR
Instructors: Sherman, A. (PI)

ENGLISH 184F: Literary Text Mining 2: Studies in Cultural Analytics

In this course, students will learn how to apply quantitative and computational methods for analyzing text to questions that are of significance to Literary Studies, and the humanities more broadly. Beginning with a series of readings and discussions on the theoretical implications of using quantitative methods for literary analysis, we will move to in-depth instruction in more advanced methods for computational text analysis, including topic models, word embeddings, and large language models. Students will not only become familiar with training and querying these models, but, more importantly, will gain hands-on experience in how to build these analytical techniques into humanities-based research.
Terms: Win | Units: 3-5 | UG Reqs: WAY-AQR, WAY-FR

ENGR 10: Introduction to Engineering Analysis

Integrated approach to the fundamental scientific principles that are the cornerstones of engineering analysis: conservation of mass, atomic species, charge, momentum, angular momentum, energy, production of entropy expressed in the form of balance equations on carefully defined systems, and incorporating simple physical models. Emphasis is on setting up analysis problems arising in engineering. Topics: simple analytical solutions, numerical solutions of linear algebraic equations, and laboratory experiences. Provides the foundation and tools for subsequent engineering courses. Prerequisite: AP Physics and AP Calculus or equivalent.
Terms: Sum | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR

ENGR 14: Intro to Solid Mechanics

Introduction to engineering analysis using the principles of engineering solid mechanics. Builds on the math and physical reasoning concepts in Physics 41 to develop skills in evaluation of engineered systems across a variety of fields. Foundational ideas for more advanced solid mechanics courses such as ME80 or CEE101A. Interactive lecture sessions focused on mathematical application of key concepts, with weekly complementary lab session on testing and designing systems that embody these concepts. Limited enrollment, subject to instructor approval. Pre-requisite: Physics 41. When signing up for this course make sure to sign up both for the lecture and for a Discussion Section.
Terms: Aut, Win, Spr | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR
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