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41 - 50 of 119 results for: all courses

ECON 179: Experimental Economics

Methods and major subject areas that have been addressed by laboratory experiments. Focus is on a series of experiments that build on one another. Topics include decision making, two player games, auctions, and market institutions. How experiments are used to learn about preferences and behavior, trust, fairness, and learning. Final presentation of group projects. Prerequisites: ECON 50, ECON 51, ECON 102A.
Terms: Win | Units: 5 | UG Reqs: WAY-AQR, WAY-SI | Grading: Letter (ABCD/NP)
Instructors: Niederle, M. (PI)

ECON 190: Introduction to Financial Accounting

How to read, understand, and use corporate financial statements. Oriented towards the use of financial accounting information (rather than the preparer), and emphasizes the reconstruction of economic events from published accounting reports.
Terms: Aut, Win | Units: 5 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

ECON 191: Introduction to Cost Accounting

Focuses on how managers use accounting information for decision making. Students will study product and service costing, activity based costing, performance management and evaluation, CVP analysis, forecasting, factors to be considered in pricing decision, capital investment analysis, and quality management and measurement.
Terms: Spr | Units: 5 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

EE 102A: Signal Processing and Linear Systems I

Concepts and tools for continuous- and discrete-time signal and system analysis with applications in signal processing, communications, and control. Mathematical representation of signals and systems. Linearity and time invariance. System impulse and step responses. System frequency response. Frequency-domain representations: Fourier series and Fourier transforms. Filtering and signal distortion. Time/frequency sampling and interpolation. Continuous-discrete-time signal conversion and quantization. Discrete-time signal processing. Prerequisite: MATH 53 or CME 102.
Terms: Win, Sum | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

EE 102B: Signal Processing and Linear Systems II

Continuation of EE 102A. Concepts and tools for continuous- and discrete-time signal and system analysis with applications in communications, signal processing and control. Analog and digital modulation and demodulation. Sampling, reconstruction, decimation and interpolation. Finite impulse response filter design. Discrete Fourier transforms, applications in convolution and spectral analysis. Laplace transforms, applications in circuits and feedback control. Z transforms, applications in infinite impulse response filter design. Prerequisite: EE 102A.
Terms: Spr | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

EE 108: Digital System Design

Digital circuit, logic, and system design. Digital representation of information. CMOS logic circuits. Combinational logic design. Logic building blocks, idioms, and structured design. Sequential logic design and timing analysis. Clocks and synchronization. Finite state machines. Microcode control. Digital system design. Control and datapath partitioning. Lab. Undergraduates must enroll for 4 units. *In Autumn, enrollment preference is given to EE majors. Formerly EE 108A.
Terms: Aut, Win | Units: 4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

EE 122B: Introduction to Biomedical Electronics

EE122B is a laboratory course covering the design and realization of key components and architectures of modern biomedical electronics systems, their application in clinical and research measurements, and practical matters in their safe reduction to practice. Material in each topic area begins with an overview of the underlying physiology. Details are presented beginning with the molecular, cellular, organ-level origins of the biosignals, followed by the relevant transduction principles, nature of the signals (amplitude, frequency spectrum, etc.), and their processing and clinical use. Specific engineering topics include safety in biomedical instruments, fundamentals of analog/digital conversion and filtering techniques for biosignals, typical transducers (biopotential, electrochemical, temperature, pressure, acoustic, movement), applications (cardiovascular medicine, neurology, pulmonology, etc.) and interfacing circuits. Prerequisite: EE122A or equivalent hands-on mixed-signal design experience and solid working knowledge of EE122A topics (see course description).
Terms: Spr | Units: 3 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter (ABCD/NP)

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 | Grading: Letter or Credit/No Credit

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 | Grading: Letter (ABCD/NP)

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. As an introduction, students in this 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.
Terms: Win | Units: 5 | UG Reqs: GER:DB-Hum, WAY-AQR | Grading: Letter (ABCD/NP)
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