Johns Hopkins University

Practical Machine Learning

This course is part of multiple programs.

Jeff Leek, PhD
Roger D. Peng, PhD
Brian Caffo, PhD

Instructors: Jeff Leek, PhD

153,597 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.5

(3,246 reviews)

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
89%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.5

(3,246 reviews)

8 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
89%
Most learners liked this course

What you'll learn

  • Use the basic components of building and applying prediction functions

  • Understand concepts such as training and tests sets, overfitting, and error rates

  • Describe machine learning methods such as regression or classification trees

  • Explain the complete process of building prediction functions

Details to know

Shareable certificate

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Assessments

5 assignments

Taught in English

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There are 4 modules in this course

This week will cover prediction, relative importance of steps, errors, and cross validation.

What's included

9 videos4 readings1 assignment

This week will introduce the caret package, tools for creating features and preprocessing.

What's included

9 videos1 assignment

This week we introduce a number of machine learning algorithms you can use to complete your course project.

What's included

5 videos1 assignment

This week, we will cover regularized regression and combining predictors.

What's included

4 videos2 readings2 assignments1 peer review

Instructors

Instructor ratings
4.5 (132 ratings)
Jeff Leek, PhD
Johns Hopkins University
32 Courses1,657,274 learners

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Recommended if you're interested in Machine Learning

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Showing 3 of 3246

4.5

3,246 reviews

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    1.78%

FF
5

Reviewed on Jul 8, 2016

MR
5

Reviewed on Aug 13, 2020

AD
5

Reviewed on Feb 28, 2017

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