University of Illinois at Urbana-Champaign
Machine Learning Algorithms with R in Business Analytics
University of Illinois at Urbana-Champaign

Machine Learning Algorithms with R in Business Analytics

This course is part of Business Analytics Specialization

Taught in English

Some content may not be translated

Ronald Guymon
Gies College of Business, University of Illinois

Instructors: Ronald Guymon

5,609 already enrolled

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

4.7

(29 reviews)

Intermediate level

Recommended experience

14 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

What you'll learn

  • 1. Conceptual framework of ML algorithms

    2. Conceptual foundation for interpreting ML results

    3. Practice applying ML algorithms to business data

Details to know

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Assessments

5 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(29 reviews)

Intermediate level

Recommended experience

14 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Business Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • 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
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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

Instructor ratings
4.8 (6 ratings)
Ronald Guymon
University of Illinois at Urbana-Champaign
5 Courses67,772 learners

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