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.
Ce cours fait partie de la Spécialisation Business Analytics
Offert par
Spécialisation Business AnalyticsUniversité de PennsylvanieÀ propos de ce cours
Résultats de carrière des étudiants
37%
44%
21%
Compétences que vous acquerrez
Résultats de carrière des étudiants
37%
44%
21%
Offert par
Université de Pennsylvanie
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
Programme du cours : ce que vous apprendrez dans ce cours
Introduction, Descriptive and Predictive Analytics
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.
Prescriptive Analytics, Low Uncertainty
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.
Predictive Analytics, Risk
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.
Prescriptive Analytics, High Uncertainty
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.
Avis
Meilleurs avis pour OPERATIONS ANALYTICS
Excellente course. Very challenging especially for beginners. The motivation to achieve my final goal of reinventing myself professionally, makes every challenge a welcome experience. Thanks Coursera!
Operations Analytics helps me to understand how to solve Newsvendor problem by statisti, forecast SUK and predict the seasonal performance. Great lessions and thanks so much for the three Instructors!
An exceptionally organized course with sufficient examples, it provides an in depth analysis of the concepts introduced (optimization, decision trees, forecasting, simulations) and of the tools used.
Course delivery, material , work sheet is excellent , I enjoyed throughout course , I had excellent learning for optimization , decision tree, simulation which will help me in my professional career.
À propos du Spécialisation Business Analytics
This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.
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