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
Online
Hybrid
Starting at $950.00
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.

Fall 2018 Schedule

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

Available
-
Instructor: Michael Chang
363209
Fee:
$950.00
43 days left. Enroll by Sep 25, 2018
See Details
Notes

Enrollment limited. Enrollment deadline: October 1, 2018. Internet access required. Materials required.

Refund Deadline
No refunds after October 8, 2018
Course Requirements
Internet access required to retrieve course materials.

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

Available
-
Thursday 6:30PM - 10:00PM
Instructor: Michael Chang
363235
Fee:
$950.00
45 days left. Enroll by Sep 27, 2018
See Details
Notes

Enrollment limited. Enrollment deadline: October 3, 2018. Internet access required. Materials required.

Refund Deadline
No refunds after October 10, 2018
Course Requirements
Internet access required to retrieve course materials.
Schedule
Type
Date
Time
Location
Computer Lab
Thu Sep 27, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Oct 4, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Oct 11, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Oct 18, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Oct 25, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Nov 1, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Nov 8, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208
Computer Lab
Thu Nov 15, 2018
6:30PM - 10:00PM
UCLA Extension Lindbrook Center
UCLA Extension Lindbrook Center 208

Contact Us

Our team members are here to help. Hours: Mon-Fri, 8am-5pm.

This course applies towards the following certificates & specializations…

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