Practical Machine Learning

( 136 Reviews )

Created by: Jeff Leek

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Overall Score : 84 / 100

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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.

Time: 14h

Instructor Details

Jeff Leek

4.2 Rating
136 Reviews

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.

Reviews

4.2

136 total reviews

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By Bernie P on 7-Aug-18

It needs to be updated. Its probably one of the most in demand skills in the field and this has a weeks worth of content 1 section 25 minutes of video 5 questions. Its just not as good as any of the other courses. 100% needs to be revamped.

By Thomas G on 7-Jun-17

By far the laziest course set up in the track. It's an interesting topic, but without independent study I would have learned almost nothing due to the lack of any "practicals" in this "Practical Machine Learning". A really disappointing course that fails to be worth more than just a couple hours of youtube.

By Jean P L on 25-Apr-18

More practice Items are needed

By Thomas B on 8-Nov-18

Lectures and course material is insufficient to get the right amount of knowledge to be able to do the tests and the course project

By Hamid M on 21-Feb-18

Unsatisfactory and poor course in this specialisation. There are many important parts which are explained inaccurately. In many cases, the lecturer jumps from important points, or assumes students have detailed knowledge about the topic. You can find ambiguity in weekly questions. Very unsatisfied!

By Grgoire M on 27-Sep-17

The worst course of the specialisation so far. The quizzes are full of typos, not clear at all, and the videos teach nothing, always refering to elements of statistical learning book. Now that I have completed the course, I do know a bunch of algorithm names involved in machine learning, but I certainly do not understand what they do and when using them.

By Andrew C on 14-May-19

The lectures and quizzes are based on old versions of R and R packages. This course needs a serious update, as some packages work differently, test answers have changed (but not been updated) and coding along with the videos results in different results. Going to the forum you can see that this has been an issue for a few years now.

By Thej K R on 4-Jun-19

Worst lectures! Worst teaching! I leanrt most of the topics on statquest. Very very very highlevel teaching, very little effort put in by Bcaffo and Rdpeng on this! So many issues in the quizzes. Wasted hours on puzzling out what is to be done! Have a look at the complaints in the course era discussion board. Issues since 3 years are not corrected. The course needs an update. But no m*****F**** is listening. Solutions to quizze are wrong! I have had it with coursera and their useles peer correction. You don't even know if what you are doing is right! Worst FEEDBACK ever!

By Erick G A on 18-Aug-17

That's a pretty rushed course. I think you really should reformulate it and discuss its content with a deeper way.

By David S on 18-Dec-18

lecture material could be cleaner with fewer errors

By Humberto R on 13-Feb-18

I was rather disappointed with this course. I guess it fills the objective of getting you using the caret package and getting you started with some examples. However to understand what you are doing you should defintively go somewhere else. I definitively missed some swirl exercises and more flow diagrams in the slides. It felt for me as I was just copypasting some code from the slides. The course does clearly give some good literature and places to go for details.

By Mariana d S e S on 1-Mar-18

Not enough context for the price payed

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