Skip to content

icon
Quality Score

Content Quality
/
Video Quality
/
Qualified Instructor
/
Course Pace
/
Course Depth & Coverage
/

Overall Score : 84 / 100

icon
Course Description

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

icon
Instructor Details

placeholder

Jeff Leek is an Assistant Professor of statistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in statistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome logy, and PLoS Medicine. He created Data Analysis as a component of the year-long statistical methods core sequence for statistics students at Johns Hopkins. The course has won a teaching excellence award, voted on by the students at Johns Hopkins, every year Dr. Leek has taught the course.

icon
More courses by Jeff Leek

Free

Free

Free

Free

Free

Free

icon
More Artificial Intelligence courses

Free

Free

Free

$79.99

Free

icon
Reviews

4.2

475 reviews in total

Select a bar to show only those reviews.Select the bar again to show every rating.

By Chris R on 15-Nov-19

Excellent course for the basics of ML

By Yadder A G on 31-Oct-19

It's the best course I've taken. It has all the basics about machine learning algorithms and more.

By Robert J C on 28-Oct-19

It gets harder but fun...R, as well Python and Matlab, can do AI well.

By Rizwan M on 13-Oct-19

great course. could have explained more techniques in caret package with coding examples

By Ashwin V on 11-Oct-19

Best course

By Ben H on 7-Oct-19

Really nice introduction to machine learning in R. You wouldn't want to pack more than this in 4 weeks. Would be interested to see if this course adopts the recipes / parsnip / tidymodels in the future.

By Michael R on 3-Oct-19

It's a mediocre intro to some machine learning tools. I think the course materials could be drastically improved.

By Connor B on 24-Sep-19

Really good exposure to machine learning and builds on the previous course in regression

By Weiqun T on 23-Sep-19

This is a very good basic course for machine learning. I got the basic ideas and skills for it.

By Robert S on 16-Sep-19

The lecture material is great, but the quiz material is in need of updating. R and it's packages have gone through many updates since the problems were written so it is sometimes difficult to reproduce their results even with running the sample codes given after getting the answer correct.

By Muhammad Z H on 15-Sep-19

learning alot

By Charbel L on 7-Sep-19

Excellent course. Shows how simple it is to start running models with machine learning...! Well done

Showing 12 of 475 reviews