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11 - 20 of 164 results for: MS&E

MS&E 111: Introduction to Optimization (ENGR 62)

Formulation and analysis of linear optimization problems. Solution using Excel solver. Polyhedral geometry and duality theory. Applications to contingent claims analysis, production scheduling, pattern recognition, two-player zero-sum games, and network flows. Prerequisite: CME 100 or MATH 51.
Terms: Aut, Spr | Units: 4 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit

MS&E 112: Mathematical Programming and Combinatorial Optimization (MS&E 212)

Combinatorial and mathematical programming (integer and non-linear) techniques for optimization. Topics: linear program duality and LP solvers; integer programming; combinatorial optimization problems on networks including minimum spanning trees, shortest paths, and network flows; matching and assignment problems; dynamic programming; linear approximations to convex programs; NP-completeness. Hands-on exercises. Prerequisites: 111 or MATH 103, CS 106A or X.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 120: Probabilistic Analysis

Concepts and tools for the analysis of problems under uncertainty, focusing on focusing on structuring, model building, and analysis. Examples from legal, social, medical, and physical problems. Topics include axioms of probability, probability trees, random variables, distributions, conditioning, expectation, change of variables, and limit theorems. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 5 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

MS&E 121: Introduction to Stochastic Modeling

Stochastic processes and models in operations research. Discrete and continuous time parameter Markov chains. Queuing theory, inventory theory, simulation. Prerequisite: 120, 125, or equivalents.
Terms: Spr | Units: 4 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit

MS&E 125: Introduction to Applied Statistics

An increasing amount of data is now generated in a variety of disciplines, ranging from finance and economics, to the natural and social sciences. Making use of this information, however, requires both statistical tools and an understanding of how the substantive scientific questions should drive the analysis. In this hands-on course, we learn to explore and analyze real-world datasets. We cover techniques for summarizing and describing data, methods for statistical inference, and principles for effectively communicating results. Prerequisite: 120, CS 106A, or equivalents.
Terms: Win | Units: 4 | Grading: Letter or Credit/No Credit

MS&E 130: Information Networks and Services

Architecture of the Internet and performance engineering of computer systems and networks. Switching, routing and shortest path algorithms. Congestion management and queueing networks. Peer-to-peer networking. Wireless and mobile networking. Information service engineering and management. Search engines and recommendation systems. Reputation systems and social networking technologies. Security and trust. Information markets. Select special topics and case studies. Prerequisites: 111, 120, and CS 106A.
Terms: Win | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter (ABCD/NP)

MS&E 135: Networks

This course provides an introduction to how networks underly our social, technological, and natural worlds, with an emphasis on developing intuitions for broadly applicable concepts in network analysis. The course will include: an introduction to graph theory and graph concepts; social networks; information networks; the aggregate behavior of markets and crowds; network dynamics; information diffusion; the implications of popular concepts such as "six degrees of separation", the "friendship paradox", and the "wisdom of crowds".
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 140: Accounting for Managers and Entrepreneurs (MS&E 240)

Non-majors and minors who have taken or are taking elementary accounting should not enroll. Introduction to accounting concepts and the operating characteristics of accounting systems. The principles of financial and cost accounting, design of accounting systems, techniques of analysis, and cost control. Interpretation and use of accounting information for decision making. Designed for the user of accounting information and not as an introduction to a professional accounting career. Enrollment limited. Admission by order of enrollment.
Terms: Aut, Win, Sum | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 140X: Financial Accounting Concepts and Analysis

Introductory course in financial accounting. Accounting is referred to as the language of business. Developing students ability to read, understand, and use business financial statements. Understanding the mapping between the underlying economic events and financial statements, and how this mapping can affect inferences about future firm profitability. Introduction to measuring and reporting of the operating cycle; the process of preparing and presenting primary financial statements; the judgment involved and discretion allowed in making accounting choices; the effects of accounting discretion on the quality of the (reported) financial information; and the fundamentals of financial statement analysis. Class time will be allocated to a combination of lectures, cases and discussions of cases. Capstone project analyzing a company's financials at the end of the quarter. Enrollment limited. Admission by order of enrollment.
Terms: Spr | Units: 2 | Grading: Satisfactory/No Credit

MS&E 145: Introductory Financial Analysis

Formerly MS&E 142. Evaluation and management of money, complicated by temporary distributions and uncertainty. The "time-value of money" and its impact on economic decisions (both personal and corporate) with the introduction of interest rate (constant or varying over time); several approaches critically examined and made consistent as suitable metrics of comparison. The concept of investment diversification in the presence of uncertainty; portfolio selection and efficient frontier analysis leading to the formulation of the Capital Asset Pricing Model; practical implementation of the concepts, including comparison of loan (e.g., house and auto) terms, credit card financial terms, interest rate term structure and its relationship to rate-of-return analysis, and graphical presentation of uncertain investment alternatives; and current economic news of interest. Critical thinking, discussion, and interaction, using group and computer labs assignments. Prerequisites: 111, 120, CME 100 or MATH 51, or equivalents.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit
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