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1 - 7 of 7 results for: engr 245

CME 245: Topics in Mathematical and Computational Finance

Description: Current topics for enrolled students in the MCF program: This course is an introduction to computational, statistical, and optimizations methods and their application to financial markets. Class will consist of lectures and real-time problem solving. Topics: Python & R programming, interest rates, Black-Scholes model, financial time series, capital asset pricing model (CAPM), options, optimization methods, and machine learning algorithms. Appropriate for anyone with a technical and solid applied math background interested in honing skills in quantitative finance. Prerequisite: basic statistics and exposure to programming.Can be repeated up to three times.
Terms: not given this year, last offered Summer 2017 | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

CS 245: Database Systems Principles

File organization and access, buffer management, performance analysis, and storage management. Database system architecture, query optimization, transaction management, recovery, concurrency control. Reliability, protection, and integrity. Design and management issues. Prerequisites: 145, 161.
Terms: not given this year, last offered Winter 2017 | Units: 3 | Grading: Letter or Credit/No Credit

CS 345S: Data-intensive Systems for the Next 1000x

The last decade saw enormous shifts in the design of large-scale data-intensive systems due to the rise of Internet services, cloud computing, and Big Data processing. Where will we see the next 1000x increases in scale and data volume, and how should data-intensive systems accordingly evolve? This course will critically examine a range of trends, including the Internet of Things, drones, smart cities, and emerging hardware capabilities, through the lens of software systems research and design. Students will perform a comparative analysis by reading and discussing cutting-edge research while performing their own original research. Prerequisites: Strong background in software systems, especially databases ( CS 245) and distributed systems ( CS 244B), and/or machine learning ( CS 229). Undergraduates who have completed CS 245 are strongly encouraged to attend.
Terms: not given this year, last offered Autumn 2016 | Units: 3-4 | Grading: Letter or Credit/No Credit

CS 349D: Cloud Computing Technology

The largest change in the computer industry over the past five years has arguably been the emergence of cloud computing: organizations are increasingly moving their workloads to managed public clouds and using new, global-scale services that were simply not possible in private datacenters. However, both building and using cloud systems remains a black art with many difficult research challenges. This research seminar will cover industry and academic work on cloud computing and survey challenges including programming interfaces, cloud native applications, resource management, pricing, availability and reliability, privacy and security. Students will also propose and develop an original research project.n nPrerequisites: For graduate students, background in computer systems ( CS 240, 244, 244B or 245) is strongly recommended. Undergrads will need instructor's approval.
Terms: Aut | Units: 3 | Grading: Letter or Credit/No Credit

ENGR 245: The Lean LaunchPad: Getting Your Lean Startup Off the Ground

Apply the "Lean Startup" principles; "business model canvas," "customer development" and "Agile Engineering" to prototype, test, and iterate your idea while discovering if you have a profitable business model. This is the class adopted by the NSF and NIH as the Innovation Corps. Apply and work in teams. Info sessions held in November and December. Team applications required in December. Proposals can be software, hardware, or service of any kind. Projects are experiential and require incrementally building the product while talking to customers/partners each week. See course website http://stanfordleanlaunchpad.weebly.com/. Prerequisite: interest and passion in exploring whether a technology idea can become a real company. Limited enrollment.
Terms: Win | Units: 3-4 | Grading: Letter (ABCD/NP)

MS&E 245A: Investment Science

Basic concepts of modern quantitative finance and investments. Focus is on the financial theory and empirical evidence that are useful for investment decisions. Topics: basic interest rates; evaluating investments: present value and internal rate of return; fixed-income markets: bonds, yield, duration, portfolio immunization; term structure of interest rates; measuring risk: volatility and value at risk; designing optimal portfolios; risk-return tradeoff: capital asset pricing model and extensions. No prior knowledge of finance is required. Concepts are applied in a stock market simulation with real data. Prerequisite: basic preparation in probability, statistics, and optimization.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit

MS&E 245B: Advanced Investment Science

Formerly MS&E 342. Topics: forwards and futures contracts, continuous and discrete time models of stock price behavior, geometric Brownian motion, Ito's lemma, basic options theory, Black-Scholes equation, advanced options techniques, models and applications of stochastic interest rate processes, and optimal portfolio growth. Computational issues and general theory. Teams work on independent projects. Prerequisite: 245A.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit
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