The Analytics Edge

Lots of interesting subjects (regression, machine learning, optimization, ...) with a practical hands-on approach.

Every discussed concepts of machine learning field was accompanied with real world problems and solutions.

Some other MOOCs had introduced even more challenging concepts (Stanford's excellent Introduction to Statistical Learning and Andrew Ng's Machine Learning course on Coursera).

This is one of the best courses on the topic of Analytics/Data Science/Machine Learning that is out there.

The course didn't disappoint, providing plenty of insight into theory and especially applications of machine learning and analytics.

I would recommend taking Coursera's Machine Learning if you'd like to learn more about underlying theory - these two courses make a great pairing.

One of the best and more thorough courses on data science.

I was thinking that it would be difficult for me to learn data science using R. But, it proved to be amazing.

Very useful class for data analysts.You learn a lot of cool R tricks and basic concepts,but if you are a student and not engaging in a data science project,it's very easy to forget everything you have learned.

If you are interested in having a first contact with R and to learn about some of the capabilities of data science, this course give a really good first idea.

If you only want to take one course to learn data science using R, take this one.

Covers key areas in data science, and opens door to future exploration.

Is very well designed, also the most fun part was the Kaggle competition where you have to put all your knowledge that you have learned in the course.

Relevant Kaggle competition.

You'll feel empowered after this course as you'll have learned quite a bit of R. I would pair this course with the first courses of Coursera's Johns Hopkins Data Science Specialization, especially R Programming, to make the Kaggle competition more manageable.

The required kaggle competition was a fun interlude, and might well have served as a gateway to a future addiction.

The best part of this course is by far the Kaggle competition.

The Kaggle competition provided by the instructors is well organized and help you to gain deep understanding of practical use cases.

Highly hands-on: you can work through all the problems following the guidance, and have experience participating in Kaggle competition.

As a consequence, results for the auto-graded Kaggle competition weren't released for two weeks and, when they came out, there was no explanation about how grades were computed, how the problem should have been approached (our independent variable was not well chosen, given the limitations of the data set), or why some students had weirdly high scores (they cheated, it turned out).

This course goes very well with Intro Statistical Learning from Stanford Online.

The homework problems for this course are very well crafted and look at a variety of interesting data sets from basketball stats to tweets about Apple.

It is very practical, very well designed, and have many applications drilled into us so that we remember.

Lot of practice exams, the concepts are drilled very well.

Very practicle and very well designed.

The way he talks through videos is just halting and uninteresting - please let the girls speak, they do it very well!

Excellent course, well structured and with very interesting case studies.

The case studies were quite unique and exhaustive.

The final exam was very well pitched and required using most of the techniques we learned during the course.

Graded course assignments include "quick questions" that accompany the lectures, a pair of problem sets for each unit, a comprehensive final exam, and a Kaggle competition that pits you against your classmates in making predictions from a data set using all you have learned during the first half of the course.

The general lack of staff communicativeness also led to grumbling about the final exam, with numerous discussion posts questioning this or that problem.

The Analytics Edge is a meaty course.

The Analytics edge is an excellent course that teaches a bunch of practical statistical tools and actually gives you enough practice using them through the lengthy homework exercises to gain some confidence with them and remember how to use them.

Taking Analytics Edge, I now have a better understanding on how to tackle problems involving data, and how to apply analytics in different fields.

The Analytics Edge (TAE) provides a solid, engaging introduction to the techniques of "big" data analysis and machine learning -- and much more.

I've completed Spring-Summer 2016 session of The Analytics Edge.

Thanks to all the instructors & support staff for a great course This courses use real world examples to teach several basic but important statistical models, in order to gain analytical edge.

The exercises and problem sets are based on real-world data, even if simplified, it was still very interesting to solve real problems with knowledge obtained from lecture.

The problem sets, while interesting, progressive and well thought out, can be tedious -- a lot of the tasks are trivial and repetitive, and it's not always clear what lesson the authors are driving at.