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#### 100% online

Start instantly and learn at your own schedule.

#### English

Subtitles: English, Korean

### What you will learn

• Describe machine learning methods such as regression or classification trees

• Explain the complete process of building prediction functions

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

• Use the basic components of building and applying prediction functions

### Skills you will gain

Random ForestMachine Learning (ML) AlgorithmsMachine LearningR Programming

#### 100% online

Start instantly and learn at your own schedule.

#### English

Subtitles: English, Korean

### Syllabus - What you will learn from this course

Week
1
2 hours to complete

## Week 1: Prediction, Errors, and Cross Validation

9 videos (Total 73 min), 4 readings, 1 quiz
9 videos
What is prediction?8m
Relative importance of steps9m
In and out of sample errors6m
Prediction study design9m
Types of errors10m
Cross validation8m
What data should you use?6m
Welcome to Practical Machine Learning10m
A Note of Explanation2m
Syllabus10m
Pre-Course Survey10m
1 practice exercise
Quiz 110m
Week
2
2 hours to complete

## Week 2: The Caret Package

9 videos (Total 96 min), 1 quiz
9 videos
Data slicing5m
Training options7m
Plotting predictors10m
Basic preprocessing10m
Covariate creation17m
Preprocessing with principal components analysis14m
Predicting with Regression12m
Predicting with Regression Multiple Covariates11m
1 practice exercise
Quiz 210m
Week
3
1 hour to complete

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

5 videos (Total 48 min), 1 quiz
5 videos
Bagging9m
Random Forests6m
Boosting7m
Model Based Prediction11m
1 practice exercise
Quiz 310m
Week
4
4 hours to complete

## Week 4: Regularized Regression and Combining Predictors

4 videos (Total 33 min), 2 readings, 3 quizzes
4 videos
Combining predictors7m
Forecasting7m
Unsupervised Prediction4m
Post-Course Survey10m
2 practice exercises
Quiz 410m
Course Project Prediction Quiz40m
4.5
508 Reviews

## 38%

started a new career after completing these courses

## 38%

got a tangible career benefit from this course

## 12%

got a pay increase or promotion

### Top reviews from Practical Machine Learning

By JCJan 17th 2017

excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

## Instructors

### Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

### Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

### Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health