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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/wharton-operations-analytics
课程评论：没有评论
课程名称：运营分析 课程概述：本课程旨在改变您将数据转化为更好决策的思维方式。随着数据收集技术的重大进步，企业在做出有效的商业决策时有了新的变化。由沃顿商学院三位顶尖专家教授的运营分析课程，重点探讨如何有效地利用数据在各种商业环境中匹配供需。本课程将教授您如何建模未来需求的不确定性、如何预测竞争政策选择的结果，以及在风险面前如何选择最佳行动方案。课程介绍了提供见解的框架和理念，涉及一系列实际商业挑战的方法，以及处理这些挑战所需的定量方法和软件，以及收集相关数据所涉及的问题。该课程适合初学者和没有分析经验的商业专业人士。 课程大纲： 1. 引言，描述性和预测性分析 - 在本模块中，您将被引入新闻贩子问题，这是一个在不确定环境中匹配供需的基本运营问题。您还将学习运营的描述性分析基础，如何利用历史需求数据构建未来需求的预测。同时，您将了解随机变量、描述性统计、常用预测工具及评估预测质量的标准等基础分析概念。 2. 指导性分析，低不确定性 - 本模块将教您如何通过建立优化模型来识别在低不确定性环境中最佳的决策，并将其应用于具体的商业挑战中。您将学习如何使用代数公式简洁地表达优化问题，如何将代数模型转换为电子表格格式，并了解如何使用电子表格求解器作为识别最佳行动方案的工具。 3. 预测性分析，风险 - 本模块将探讨如何在不确定的情况下评估和比较决策的影响。您将学习如何构建和解释模拟模型，以帮助您评估复杂的商业决策。在这一周，您将接触一些常见的风险和回报度量，使用模拟估计这些量，并学习如何解释和可视化您的模拟结果。 4. 指导性分析，高不确定性 - 本模块介绍决策树，这是评估不确定性下决策的有用工具。通过具体示例，您将学习如何将优化、模拟和决策树结合起来解决高不确定性下的复杂商业问题。您还将发现如何利用在第一周引入的新闻贩子问题并结合第二、三周引入的模拟和优化框架进行解决。
Name:Introduction, Descriptive and Predictive Analytics
Description:In this module you’ll be introduced to the Newsvendor problem, a fundamental operations problem of matching supply with demand in uncertain settings. You'll also cover the foundations of descriptive analytics for operations, learning how to use historical demand data to build forecasts for future demand. Over the week, you’ll be introduced to underlying analytic concepts, such as random variables, descriptive statistics, common forecasting tools, and measures for judging the quality of your forecasts.
Name:Prescriptive Analytics, Low Uncertainty
Description:In this module, you'll learn how to identify the best decisions in settings with low uncertainty by building optimization models and applying them to specific business challenges. During the week, you’ll use algebraic formulations to concisely express optimization problems, look at how algebraic models should be converted into a spreadsheet format, and learn how to use spreadsheet Solvers as tools for identifying the best course of action.
Name:Predictive Analytics, Risk
Description:How can you evaluate and compare decisions when their impact is uncertain? In this module you will learn how to build and interpret simulation models that can help you to evaluate complex business decisions in uncertain settings. During the week, you will be introduced to some common measures of risk and reward, you’ll use simulation to estimate these quantities, and you’ll learn how to interpret and visualize your simulation results.
Name:Prescriptive Analytics, High Uncertainty
Description:This module introduces decision trees, a useful tool for evaluating decisions made under uncertainty. Using a concrete example, you'll learn how optimization, simulation, and decision trees can be used together to solve more complex business problems with high degrees of uncertainty. You'll also discover how the Newsvendor problem introduced in Week 1 can be solved with the simulation and optimization framework introduced in Weeks 2 and 3.
This course is designed to impact the way you think about transforming data into better decisions. Recent extraordinary improvements in data-collecting technologies have changed the way firms make informed and effective business decisions. The course on operations analytics, taught by three of Wharton’s leading experts, focuses on how the data can be used to profitably match supply with demand in various business settings. In this course, you will learn how to model future demand uncertainties, how to predict the outcomes of competing policy choices and how to choose the best course of action in the face of risk. The course will introduce frameworks and ideas that provide insights into a spectrum of real-world business challenges, will teach you methods and software available for tackling these challenges quantitatively as well as the issues involved in gathering the relevant data. This course is appropriate for beginners and business professionals with no prior analytics experience.
