About this Course

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Flexible deadlines
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Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Approx. 8 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 Forest
  • Machine Learning (ML) Algorithms
  • Machine Learning
  • R Programming
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. 8 hours to complete
English

Offered by

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Johns Hopkins University

Syllabus - What you will learn from this course

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Week1
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
Week2
Week 2
2 hours to complete

Week 2: The Caret Package

2 hours to complete
9 videos (Total 96 min)
Week3
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)
Week4
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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