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41 - 50 of 56 results for: MS&E ; Currently searching spring courses. You can expand your search to include all quarters

MS&E 324: Stochastic Methods in Engineering (CME 308, MATH 228)

The basic limit theorems of probability theory and their application to maximum likelihood estimation. Basic Monte Carlo methods and importance sampling. Markov chains and processes, random walks, basic ergodic theory and its application to parameter estimation. Discrete time stochastic control and Bayesian filtering. Diffusion approximations, Brownian motion and an introduction to stochastic differential equations. Examples and problems from various applied areas. Prerequisites: exposure to probability and background in analysis.
Terms: Spr | Units: 3

MS&E 334: Topics in Social Data

This Ph.D. course will study advanced topics in causal inference, with a focus on nuances of experimental design and policy evaluation, particularly in settings with interference. We will emphasize discussion of a range of experimental designs, as well as applications in networks and marketplaces. The course will be taught in a seminar format, with an emphasis on in-depth discussion of recent research papers at the frontiers of this area. The class is restricted to Ph.D. students; exceptions require instructor approval.
Terms: Spr | Units: 3

MS&E 338: Aligning Superintelligence

Within a couple of decades, or less, it is plausible that humans will create an AI that is much smarter than humans in practically all domains of human activity. We refer to such an AI as a superintelligence. The alignment problem is how to make sure that such a superintelligence acts according to its creator's intent. This course is intended for a technical audience interested in thinking about this problem. Prerequisites: one graduate-level machine learning course and one course that studies agents (e.g., AI, RL, decision analysis, economics).
Terms: Spr | Units: 3 | Repeatable 4 times (up to 12 units total)

MS&E 349: Financial Statistics

Topics in financial statistics with focus on current research: Time-series modeling, volatility modeling, high-frequency statistics, large-dimensional factor modeling and estimation of continuous-time processes. Prerequisites: 220, 226 or STATS 200, 221 or STATS 217, 245A, or equivalents.
Terms: Spr | Units: 3

MS&E 386: Doctoral Research Seminar on Technology & Organizations (SOC 360)

Doctoral Research Seminar on Technology & Organizations
Terms: Spr | Units: 1-3

MS&E 390: Doctoral Research Seminar in Health Systems Modeling (HRP 390)

Restricted to PhD students, or by consent of instructor. Doctoral research seminar covering current topics in health policy, health systems modeling, and health innovation. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit
Instructors: Brandeau, M. (PI)

MS&E 394: Advanced Methods in Modeling for Climate and Energy Policy

Design and application of computational models and techniques for assessing climate and energy policy, and for predicting the impacts of climate change. Topics include 1) best practices in research design, model design and selection; 2) types of models available, taxonomy, core concepts, and limitations; 3) interpreting and presenting model results; and 4) advanced topics and recent literature, e.g. representing uncertainty, technological change, distributional change, and cross-sectoral climate impacts. Prerequisites: MS&E 241, MS&E 211, or equivalents.
Terms: Spr | Units: 3
Instructors: Weyant, J. (PI)

MS&E 408: Directed Reading and Research

Directed reading and research on a subject of mutual interest to student and faculty member. Available to undergraduate, master, and doctoral students. Student must clarify deliverables, units, and grading basis with faculty member before applicable deadlines. Prerequisite: consent of instructor
Terms: Aut, Win, Spr, Sum | Units: 1-10 | Repeatable for credit

MS&E 447: Blockchain Technologies & Entrepreneurship

This course offers a concise, in-depth exploration of entrepreneurship in decentralized computing, focusing on the rapid advance of decentralized blockchain technology since Bitcoin's release in 2009. We'll examine relevant technological advancements and their market opportunities in finance, AI, social media, gaming, and open computing. Discussions will differentiate lasting innovations from transient trends, helping students sort real advances from headline-grabbing volatility, speculation, and fraud. The course features guest speakers from top blockchain startups and venture capital firms, fostering actionable real-world insights. Key topics include blockchain foundations, emerging trends in scalable infrastructure, AI, verifiable computation, Decentralized Finance (DeFi), Real World Assets (RWA), decentralized governance (e.g. DAOs), and Decentralized Physical Infrastructure (DePIN). The course will equip students with foundational knowledge for potential entrepreneurial ventures based on distributed computing.
Terms: Spr | Units: 1 | Repeatable 12 times (up to 12 units total)

MS&E 454: Decision Analysis Seminar

Current research and related topics presented by doctoral students and invited speakers. May be repeated for credit. Prerequisite: 252.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit
Instructors: Shachter, R. (PI)
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