DataRobot Case Studies DataRobot In the Classroom

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	DataRobot In the Classroom DataRobot

DataRobot In the Classroom

DataRobot

Technology Category	Analytics & Modeling - Machine Learning
Applicable Industries	Education
Applicable Functions	Product Research & Development
Use Cases	Predictive Maintenance
Services	Training
Challenge	Smith School of Business at Queen’s University in Canada is known for its innovative approach to business education, including creating ground-breaking programs and courses in emerging areas including artificial intelligence, fintech, analytics, cultural diversity, team dynamics, social impact and more. Anton Ovchinnikov, Distinguished Professor of Management Analytics at the Smith School of Business, teaches courses in predictive modeling, data science and machine learning. His students are typically working professionals who are consumers of analytics, not producers. Many of them are, or will soon be, managers of analytical projects and teams. As part of Anton’s courses, he wants his students to familiarize themselves with the raw coding, at least at a basic level, in order to fully understand what’s behind the curtain of what they’re trying to predict. However, the manual coding process can be time-consuming and complex, leading to a need for a more efficient solution. Read More
About Customer	The customer in this case study is the Smith School of Business at Queen’s University in Canada. Established in 1919 and located in Kingston, Ontario, the school has received international recognition for its innovative approach to business education. This includes creating ground-breaking programs and courses in emerging areas such as artificial intelligence, fintech, analytics, cultural diversity, team dynamics, social impact and more. The students at the school are typically working professionals who are consumers of analytics, not producers. Many of them are, or will soon be, managers of analytical projects and teams. Read More
Solution	Anton introduced his students to DataRobot’s automated machine learning platform. The platform was used in the context of a case study on Retention Modeling at a Scholastic Travel Company, which is a retention modeling exercise focused on predicting customer churn. After a week of working on the case assignment by manually coding predictive models, the students were introduced to how DataRobot and automation can be a solution. The students then had access to the DataRobot platform to play around with for a limited time. According to Anton, a number of them found automated machine learning to be so valuable that they began commercial evaluations at their companies. This solution not only provided the students with a practical understanding of automated AI applications but also equipped them with a valuable tool for their future careers. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Applicable Industries

Education

Applicable Functions

Product Research & Development

Use Cases

Predictive Maintenance

Services

Training

Challenge

Smith School of Business at Queen’s University in Canada is known for its innovative approach to business education, including creating ground-breaking programs and courses in emerging areas including artificial intelligence, fintech, analytics, cultural diversity, team dynamics, social impact and more. Anton Ovchinnikov, Distinguished Professor of Management Analytics at the Smith School of Business, teaches courses in predictive modeling, data science and machine learning. His students are typically working professionals who are consumers of analytics, not producers. Many of them are, or will soon be, managers of analytical projects and teams. As part of Anton’s courses, he wants his students to familiarize themselves with the raw coding, at least at a basic level, in order to fully understand what’s behind the curtain of what they’re trying to predict. However, the manual coding process can be time-consuming and complex, leading to a need for a more efficient solution.

About Customer

The customer in this case study is the Smith School of Business at Queen’s University in Canada. Established in 1919 and located in Kingston, Ontario, the school has received international recognition for its innovative approach to business education. This includes creating ground-breaking programs and courses in emerging areas such as artificial intelligence, fintech, analytics, cultural diversity, team dynamics, social impact and more. The students at the school are typically working professionals who are consumers of analytics, not producers. Many of them are, or will soon be, managers of analytical projects and teams.

Solution

Anton introduced his students to DataRobot’s automated machine learning platform. The platform was used in the context of a case study on Retention Modeling at a Scholastic Travel Company, which is a retention modeling exercise focused on predicting customer churn. After a week of working on the case assignment by manually coding predictive models, the students were introduced to how DataRobot and automation can be a solution. The students then had access to the DataRobot platform to play around with for a limited time. According to Anton, a number of them found automated machine learning to be so valuable that they began commercial evaluations at their companies. This solution not only provided the students with a practical understanding of automated AI applications but also equipped them with a valuable tool for their future careers.

Impact #1	The students were able to understand the practical application of automated AI.
Impact #2	The students gained hands-on experience with a leading automated machine learning platform.
Impact #3	The students were able to see the efficiency and accuracy of automated machine learning in action.

Impact #1

The students were able to understand the practical application of automated AI.

Impact #2

The students gained hands-on experience with a leading automated machine learning platform.

Impact #3

The students were able to see the efficiency and accuracy of automated machine learning in action.

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Overview

DataRobot In the Classroom

Operational Impact