About this Course

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Learner Career Outcomes

37%

started a new career after completing these courses

37%

got a tangible career benefit from this course

12%

got a pay increase or promotion
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Approx. 9 hours to complete
English

What you will 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

Skills you will gain

Random ForestMachine Learning (ML) AlgorithmsMachine LearningR Programming

Learner Career Outcomes

37%

started a new career after completing these courses

37%

got a tangible career benefit from this course

12%

got a pay increase or promotion
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Approx. 9 hours to complete
English

Offered by

Placeholder

Johns Hopkins University

Syllabus - What you will learn from this course

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Week
1

Week 1

2 hours to complete

Week 1: Prediction, Errors, and Cross Validation

2 hours to complete
9 videos (Total 73 min), 4 readings, 1 quiz
Week
2

Week 2

2 hours to complete

Week 2: The Caret Package

2 hours to complete
9 videos (Total 96 min)
Week
3

Week 3

1 hour to complete

Week 3: Predicting with trees, Random Forests, & Model Based Predictions

1 hour to complete
5 videos (Total 48 min)
Week
4

Week 4

3 hours to complete

Week 4: Regularized Regression and Combining Predictors

3 hours to complete
4 videos (Total 33 min), 2 readings, 3 quizzes

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