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Operations Analytics

Approx. 10 hours to complete

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Course Summary

This course on Operations Analytics will teach you how to apply analytical techniques to real-world business problems and make data-driven decisions.

Key Learning Points

Learn how to use data to identify opportunities for improvement in business operations
Use optimization techniques to make the most out of limited resources
Understand how analytics can help improve supply chain management and overall business performance

Learning Outcomes

Apply analytical techniques to real-world business problems
Make data-driven decisions to improve business operations
Optimize limited resources to achieve better business performance

Prerequisites or good to have knowledge before taking this course

Basic knowledge of statistics and probability
Familiarity with spreadsheet software such as Excel

Course Difficulty Level

Intermediate

Course Format

Online self-paced
Video lectures
Assignments and quizzes

Similar Courses

Business Analytics Fundamentals
Supply Chain Analytics
Data Science Essentials

Related Education Paths

Notable People in This Field

Author and Professor, Babson College
Founder, FiveThirtyEight

Related Books

Description

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.

Outline

Introduction, Descriptive and Predictive Analytics
Course Introduction and Welcome
The Newsvendor Problem
Moving Averages
Trends, Seasonality
Week 1 Wrap-up, Apparel Industry
Excel Files, Slides and Practice Problems
Newsvendor and Forecasting Quiz

Prescriptive Analytics, Low Uncertainty
How to Build an Optimization Model
Optimizing with Solver
Network Optimization Example
(Optional) Week 2 Review
(Optional) Solver on Mac
(Optional) Solver in Google Sheets
Excel Files, Slides, and Practice Problems
Decisions with Low Uncertainty Quiz

Predictive Analytics, Risk
Comparing Decisions in Uncertain Settings
Simulating Uncertain Outcomes in Excel
Interpreting and Visualizing Simulation Output
(Optional) Week 3 Review
Excel file, Slides, Practice Problems
Risk and Evaluation Quiz

Prescriptive Analytics, High Uncertainty
Decision Trees
Using Simulation with Decision Trees
Using Optimization Together with Simulation
Week 4 Wrap-up
(Optional) Session 4 Review
(Optional) Advanced Session on Optimization
Excel files, Slides, and Practice Problems
Decision Tree Analysis Quiz

Summary of User Reviews

Discover Wharton's Operations Analytics course on Coursera, highly rated by learners. This course is designed to help learners understand and apply key principles of operations management, as well as use analytics to improve business performance.

Key Aspect Users Liked About This Course

Many users appreciated the course's clear explanations and practical applications of operations analytics concepts.

Pros from User Reviews

Clear explanations of complex concepts
Real-world case studies and examples
Engaging and knowledgeable instructors
Flexible pacing and scheduling options
Hands-on assignments and exercises

Cons from User Reviews

Some learners found the course material too challenging or technical
Limited opportunities for interaction with instructors or peers
Some technical issues with the online learning platform
Limited feedback on assignments and assessments
Some learners would have preferred more in-depth coverage of certain topics

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