2016-2017 2017-2018 2018-2019 2019-2020 2020-2021
by subject...
  COVID-19 Scheduling Updates!
See Stanford's HealthAlerts website for latest updates concerning COVID-19 and academic policies.

1 - 8 of 8 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.
Last offered: Summer 2017 | Repeatable 3 times (up to 3 units total)

CS 245: Principles of Data-Intensive Systems

Most important computer applications have to reliably manage and manipulate datasets. This course covers the architecture of modern data storage and processing systems, including relational databases, cluster computing frameworks, streaming systems and machine learning systems. Topics include storage management, query optimization, transactions, concurrency, fault recovery, and parallel processing, with a focus on the key design ideas shared across many types of data-intensive systems. Prerequisites: CS 145, 161.
Terms: Win | Units: 3

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.
Last offered: Autumn 2016

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.
Last offered: Autumn 2018

DESINST 245: Redesigning Post-Disaster Finance

Unfortunately, natural disaster scenarios are becoming annual and severe due to climate change, urbanization and legacy building practices and standards. When disaster responders leave affected communities, banks, insurance companies and government agencies are challenged to fund the rebuilding.nnHow might we bring human-centered design to the post-disaster loan and insurance processes?nnIn this class, you will interview bankers, insurers and their bank regulators, borrowers, past disaster victims, emergency responders and others to visually map post-disaster process from multiple points-of-view, with the goal of revealing simpler and more adaptive design opportunities.Then you will work together to produce an immersive storytelling experience for all stakeholders to see how they might take a more human-centered approach to the post-disaster banking and insurance processes, where the stories of rebuilt community and household can be better told, shared and funded faster.nnAdmission by application. Find more info at dschool.stanford.edu/classes.
Terms: Spr | Units: 3-4

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

Learn how to turn a technical idea from a lab, research, or vision into a successful business using the Lean Launchpad process (business model canvas, customer development, running experiments, and agile engineering.) Hands-on experiential class. 15+ hours per week talking to customers, regulators and partners outside the classroom, plus time building minimal viable products. This class is the basis of the National Science Foundation I-Corps ¿ with a focus on understanding all the components to build for deep technology and life science applications. Team applications required in March. Proposals may be software, hardware, or service of any kind. See course website http://leanlaunchpad.stanford.edu/. Prerequisite: interest in and passion for exploring whether your technology idea can become a real company. Limited enrollment.
Terms: Win, Spr | Units: 3-4

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

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: Spr | Units: 3
Filter Results:
term offered
updating results...
teaching presence
updating results...
number of units
updating results...
time offered
updating results...
updating results...
UG Requirements (GERs)
updating results...
updating results...
updating results...
© Stanford University | Terms of Use | Copyright Complaints