Machine Learning Using R

COM SCI X 450.41

Learn machine learning origins, principles, and practical applications, as well as implementation via the R programming language. Students will learn to train a model, evaluate its performance, and improve its performance.

READ MORE ABOUT THIS COURSE
Fall
Winter
Spring
Summer
Online
In Person
Starting at $1,095.00
As few as 11 weeks
4.0

What you can learn.

  • Collect, explore, visualize, and prepare data for machine learning problems using R
  • Understand how machine learning algorithms make predictions
  • Identify appropriate machine learning algorithms for your project
  • Train, evaluate, monitor, and improve machine learning models
  • Implement machine learning solutions

About this course:

This course introduces machine learning using R. Students will learn structured and unstructured data processing, linear regression modeling and non-linear modeling methods used in machine learning algorithm development, optimization techniques, neural networks, and deep learning. This field is made possible due to the rapid and simultaneous evolution of available data, statistical methods, and computing power. 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 who are used to construct predictive models and unsupervised learners who 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. A foundational understanding of coding, particularly in R, is necessary for success in this course.
Prerequisites

Before embarking on the Machine Learning course, it is imperative to establish a robust foundational knowledge. We suggest the following preparatory steps: Introduction to Data Science to acquaint yourself with the basic principles of data science.

 

Statistics Background: In case you lack proficiency in statistics, we recommend enrolling in a course such as Introduction to Statistical Reasoning. Grasping statistical concepts is a key determinant of success in machine learning.

 

Foundational understanding of coding, particularly in R, is necessary for success in this course.

Fall 2024 Schedule

Date & Time
Details
Format
 
-
Tuesday 6:00PM - 9:00PM PT
Enrollment Closed
See Details
Instructor: Tim Park
400112
Fee:
$1,095.00
In Personformat icon
Location: UCLA
Notes

Enrollment limited; early enrollment advised. Visitors not permitted.

Enrollment deadline: October 7th, 2024

Refund Deadline
No refunds after September 28, 2024
Schedule
Type
Date
Time
Location
Discussion
Tue Sep 24, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Oct 1, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Oct 8, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Oct 15, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Oct 22, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Oct 29, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Nov 5, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Nov 12, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Nov 19, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Nov 26, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
Discussion
Tue Dec 3, 2024
6:00PM PT - 9:00PM PT
UCLA
Haines Hall A24
-
This section has no set meeting times.
Canceled
See Details
Instructor: Stefan Lin
399633
Fee:
$1,095.00
Onlineformat icon
Notes

Enrollment limited; early enrollment advised. Enrollment deadline: October 7th, 2024

Refund Deadline
No refunds after September 27, 2024

Winter 2025 Schedule

Date & Time
Details
Format
 
-
Tuesday 6:00PM - 9:00PM PT
Future Offering (Opens November 04, 2024 12:00:00 AM)
See Details
Instructor: Tim Park
400715
Fee:
$1,095.00
In Personformat icon
Location: UCLA Extension Gayley Center in Westwood
Notes

Enrollment limited; early enrollment advised. Visitors not permitted.

Enrollment deadline: January 20th, 2025

Refund Deadline
No refunds after January 20, 2025
Schedule
Type
Date
Time
Location
Discussion
Tue Jan 7, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Jan 14, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Jan 21, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Jan 28, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Feb 4, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Feb 11, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Feb 18, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Feb 25, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Mar 4, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Mar 11, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
Discussion
Tue Mar 18, 2025
6:00PM PT - 9:00PM PT
UCLA Extension Gayley Center in Westwood
UCLA Extension Gayley Center 121E
-
This section has no set meeting times.
Future Offering (Opens November 04, 2024 12:00:00 AM)
See Details
Instructor: Stefan Lin
400714
Fee:
$1,095.00
Onlineformat icon
Notes

Enrollment limited; early enrollment advised. Enrollment deadline: January 20th, 2025

Refund Deadline
No refunds after January 10, 2025

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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