One of the most exciting aspects of business analytics is finding patterns in the data using machine learning algorithms. In this course you will gain a conceptual foundation for why machine learning algorithms are so important and how the resulting models from those algorithms are used to find actionable insight related to business problems. Some algorithms are used for predicting numeric outcomes, while others are used for predicting the classification of an outcome. Other algorithms are used for creating meaningful groups from a rich set of data. Upon completion of this course, you will be able to describe when each algorithm should be used. You will also be given the opportunity to use R and RStudio to run these algorithms and communicate the results using R notebooks.
Machine Learning Algorithms with R in Business Analytics
This course is part of Business Analytics Specialization
Instructors: Ronald Guymon
7,210 already enrolled
Included with 
(38 reviews)
Recommended experience
What you'll learn
Implement a conceptual framework of machine learning algorithms for finding actionable insight to business problems.
Apply a conceptual foundation for interpreting machine learning results from regression, classification, and clustering algorithms.
Apply machine learning algorithms to business data.
Skills you'll gain
Details to know
Add to your LinkedIn profile
5 quizzes
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 4 modules in this course
Exploratory data analysis (EDA) is a critical step in the business analytic workflow; however, EDA is a time-consuming approach for uncovering complex relationships. Moreover, the visualizations that are often used for EDA do not lend themselves well for quantifying confidence in results or for making predictions.
What's included
15 videos6 readings2 quizzes1 peer review1 discussion prompt1 plugin
Gain an understanding of machine learning in business and logistic regression
What's included
14 videos2 readings1 quiz
Classification algorithms in general, K-nearest neighbors, and decision trees.
What's included
12 videos2 readings1 quiz
Clustering algorithms, k-means, and DBSCAN
What's included
13 videos4 readings1 quiz1 discussion prompt1 plugin
Instructors
Offered by
Recommended if you're interested in Leadership and Management
Coursera Project Network
CertNexus
Build toward a degree
This course is part of the following degree program(s) offered by University of Illinois Urbana-Champaign. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
Why people choose Coursera for their career
New to Leadership and Management? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). If you choose to explore the course without purchasing, you may not be able to access certain assignments.
You will be eligible for a full refund until 2 weeks after your payment date. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the 2-week refund period.
Yes! Coursera provides financial aid to learners who would like to complete a course but cannot afford the course fee. To apply for aid, select "Learn more and apply" in the Financial Aid section below the "Enroll" button. You'll be prompted to complete a simple application; no other paperwork is required.