Information Technology
Hands on Training icon
Hands On Training
Hands on Training icon

Supervised Learning in R: Classification

Course Cover

5

(3)

compare button icon

Course Features

icon

Duration

4 hours

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Mobile, Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

4 hours

Course Description

This introduction to machine-learning is intended for beginners. It covers four of the most well-known classification algorithms. This course will provide a solid understanding of the approach each algorithm takes to learning tasks and the R functions that are required to apply these tools to your own work.

blur
blur

Highlights

blur

Pedagogy

Top 30 Percentile

blur

Rating & Reviews

Top 30 Percentile

blur

Parameters

cv-icon

Pedagogy

Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

cv-icon

Rating & Reviews

This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.

Course Overview

projects-img

Virtual Labs

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Intermediate R

What You Will Learn

You will come away with a basic understanding of how each algorithm approaches a learning task, as well as learn the R functions needed to apply these tools to your own work

This chapter will provide an overview of the technique while illustrating how to apply it to fundraising data

Course Instructors

Author Image

Brett Lantz

Data Scientist at the University of Michigan

Brett Lantz is a data scientist at the University of Michigan and the author of Machine Learning with R. After training as a sociologist, Brett has applied his endless thirst for data to projects tha...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

Course Cover