Name: Clustering, Classification, and Machine Learning in R
Availability: InStock

Course Overview

When faced with a large volume of unstructured data, the question quickly arises: what does this all mean? Techniques in machine learning offer the promise of a meaningful answer to that question. Unsupervised machine learning is a powerful tool that is being put to use in many disciplines. In this course, you'll experience machine learning through scripting in the statistical programming language R.

The course focuses on using unsupervised machine learning to bring coherence to unstructured data. Specifically, you'll use different methods to generate clusters within your data set when no dependent variable is specified. Using supervised machine learning approaches, you'll build and evaluate models that allow you to classify your data and understand the marginal impacts of each attribute. And you'll gain experience with powerful tools in R that allow you to efficiently evaluate competing models to find the one that gives you the most accurate results.

You are required to have completed the following course or have equivalent experience before taking this course:

Predictive Analytics in R

Key Course Takeaways

Create clusters for structured data with no specified dependent variable
Choose appropriate models and methods for classifying items in a set
Apply and compare many solution methods simultaneously

Discover More

Download a Brochure

Not ready to enroll but want to learn more? Download the course brochure to review program details.

Download Now

How It Works

Effort

3 to 5 hours of study per week

Format

100% online, instructor-led

Course Author

view details

Chris Anderson

Professor, EMMH Program Director

Cornell Nolan School of Hotel Administration

Professor, Nolan School of Hotel Administration, Cornell SC Johnson College of Business

Chris Anderson is a professor at the Cornell Nolan School of Hotel Administration. Prior to his appointment in 2006, he was on the faculty at the Ivey School of Business in London, Ontario, Canada.

Professor Anderson’s main research focus is on revenue management and service pricing. He actively works in the application and development of revenue management across numerous industry types, including hotels, airlines, and rental car and tour companies, as well as numerous consumer packaged goods and financial services firms.

Professor Anderson’s research has been funded by numerous governmental agencies and industrial partners. He serves on the editorial board of the Journal of Revenue and Pricing Management and is the regional editor for the International Journal of Revenue Management.

At the Nolan School of Hotel Administration, Professor Anderson teaches courses in revenue management and service operations management.

Who Should Enroll

Analysts
Developers
Data scientists
Functional managers
Consultants
Any professional that uses data to make business decisions

Get It Done
100% Online

Our programs are expressly designed to fit the lives of busy professionals like you.

Learn From
cornell's Top Minds

Courses are personally developed by faculty experts to help you gain today's most in-demand skills.

Power Your
career

Cornell's internationally recognized standard of excellence can set you apart.

Stack To A Certificate

Data Analytics in R

Request Information Now by completing the form below.

Act today—courses are filling fast.

Do you wish to communicate with our team by text message?

I'm most interested in programs about: *