Rutgers the State University of New Jersey

Demand Analytics

Yao Zhao

Instructor: Yao Zhao

21,032 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(284 reviews)

Beginner level
No prior experience required
14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.6

(284 reviews)

Beginner level
No prior experience required
14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Use data analytics to predict demand with trend (as in new product introduction), seasonality, price elasticity and other environmental factors.

  • Identify the key drivers for demand and quantify their impact.

  • Build, validate and improve forecasting models with both continuous and categorical variables.

Details to know

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Assessments

5 assignments

Taught in English

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This course is part of the Supply Chain Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

Welcome to the exciting world of Demand Analytics! In Week 1, you will learn the crisis that AK MetalCrafters (a leading cookware manufacturer in North America) faced in launching new products, and how AK successfully resolved the crisis using Demand Analytics. You will also learn the general principles of demand planning and forecasting, and how it fits into a firm's integrated business planning.

What's included

3 videos2 readings1 assignment1 peer review1 discussion prompt

Welcome to Week 2 of Demand Analytics! In Week 1, you learned the general principles, now in Week 2, you will put them to action by building and interpreting a linear model for predicting the trend (as in new product introduction). You will also learn data collection, pre-processing and visualization techniques, which are critical to model building.

What's included

5 videos3 readings1 assignment2 peer reviews

Welcome to Week 3 of Demand Analytics! In Week 2, you built a linear model to predict the trend. In this week, you will validate and improve the model by first analyzing its errors to identify missing variables and then building a multiple regression model to capture not only the trend but also the impact of price and other environmental factors.

What's included

3 videos1 reading2 assignments1 peer review

In this last week of Demand Analytics, you will further improve your demand forecasting model built in Week 3 by including seasonality to capture the periodic patterns in the errors; you will learn how to model and format categorical variables, and how to create and test your forecast.

What's included

3 videos2 readings1 assignment1 peer review1 discussion prompt

Instructor

Instructor ratings
4.6 (77 ratings)
Yao Zhao
6 Courses90,497 learners

Recommended if you're interested in Business Essentials

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Learner reviews

4.6

284 reviews

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