Machine Learning Using R

COM SCI X 450.4
This course focuses on using the language R for machine learning, which is concerned with algorithms that transform information into actionable intelligence.
READ MORE ABOUT THIS COURSE
Fall
Winter
Spring
Summer
Online
Hybrid
Starting at $995.00
As few as 10 weeks
4.0 Credits
3.3 CEUs

What you can learn.

  • Learn how to collect data and explore and prepare the data for the machine learning algorithm
  • Learn how to select the appropriate machine learning algorithm for the data and proposed task
  • Learn how to train a model, and evaluate and improve the model performance

About this course:

This course focuses on machine learning, which is concerned with algorithms that transform information into actionable intelligence. This field is made possible due to the rapid and simultaneous evolution of available data, statistical methods and computing power. The machine learning language, R, is a cross-platform, zero-cost statistical programming environment, which offers a powerful but easy-to-learn set of tools that can assist students with finding data insights. Students learn the origins and practical applications of machine learning, how knowledge is defined and represented by computers, and the basic concepts that differentiate machine learning approaches. Machine learning algorithms can be divided into two main groups: supervised learners that are used to construct predictive models, and unsupervised learners that are used to build descriptive models. Students learn the classification, numeric predictor, pattern detection, and clustering algorithms. Students learn to train a model, evaluate its performance, and improve its performance. Algorithm uses are illustrated with real-world cases, such as breast cancer diagnosis, spam filtering, identifying bank loan risk, predicting medical expenses, estimating wine quality, identifying groceries frequently purchased together, and finding teen market segments.
Suggested Prerequisites

It is advisable that you complete the following (or equivalent) since they are prerequisites for Machine Learning Using R.

Prior knowledge in R, COM SCI X 450.1 Introduction to Data Science, or consent of instructor.

Spring 2019 Schedule

These courses are fully online, and there are no in-person classroom meetings.

Enrollment Closed
-
Instructor: Michael Chang
367166
Fee:
$995.00
See Details
Notes

Enrollment limited. Enrollment deadline: April 10, 2019. Internet access required. Materials required.

Refund Deadline
No refunds after April 17, 2019
Course Requirements
Machine Learning with R - Second Edition by Brett Lantz
(Optional) R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data and Analytics) by Jared Lander
Internet access required to retrieve course materials.

Hybrid courses utilize a combination of in-person classroom meetings and online meetings.

Enrollment Closed
-
Thursday 6:00PM - 9:30PM
367167
Fee:
$995.00
See Details
Notes

Enrollment limited. Enrollment deadline: April 10, 2019. Internet access required. Materials required.

Refund Deadline
No refunds after April 24, 2019
Course Requirements
Machine Learning with R - Second Edition by Brett Lantz
(Optional) R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data and Analytics) by Jared Lander
Internet access required to retrieve course materials.
Schedule
Type
Date
Time
Location
Computer Lab
Thu Apr 11, 2019
6:00PM - 9:30PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Apr 25, 2019
6:00PM - 9:30PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu May 9, 2019
6:00PM - 9:30PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu May 23, 2019
6:00PM - 9:30PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Jun 6, 2019
6:00PM - 9:30PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208

These courses are fully online, and there are no in-person classroom meetings.

Future Offering (Opens 29 Apr 2019 12:00:00 AM)
-
368412
Fee:
$995.00
See Details
Notes

Enrollment limited. Enrollment deadline: June 30, 2019. Internet access required. Materials required.

Refund Deadline
No refunds after July 7, 2019
Course Requirements
Machine Learning with R - Second Edition by Brett Lantz
(Optional) R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data and Analytics) by Jared Lander
Internet access required to retrieve course materials.

Hybrid courses utilize a combination of in-person classroom meetings and online meetings.

Future Offering (Opens 29 Apr 2019 12:00:00 AM)
-
Thursday 6:30PM - 10:00PM
368413
Fee:
$995.00
See Details
Notes

Enrollment limited. Enrollment deadline: July 3, 2019. Internet access required. Materials required.

Refund Deadline
No refunds after July 10, 2019
Course Requirements
Machine Learning with R - Second Edition by Brett Lantz
(Optional) R for Everyone: Advanced Analytics and Graphics (Addison-Wesley Data and Analytics) by Jared Lander
Internet access required to retrieve course materials.
Schedule
Type
Date
Time
Location
Computer Lab
Thu Jun 27, 2019
6:30PM - 10:00PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Jul 11, 2019
6:30PM - 10:00PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Jul 25, 2019
6:30PM - 10:00PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Aug 8, 2019
6:30PM - 10:00PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Aug 22, 2019
6:30PM - 10:00PM
UCLA Extension Lindbrook Center in Westwood
UCLA Extension Lindbrook Center 208

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