Does the job of a good introduction.

Very limited and restrictive practice and assinments.

For a true learning experience one needs to do a lot of external research and work to show a measureable benifit.

The content is good but there are a lot of mistakes and typos in the material. The peer review is extremely vulnerable to errors - only one person reviewed my assignment and gave me the wrong mark.

Useful course but riddled with typos & inconsistent questions and answers. Needs a proper review by someone (probably not the people answering on the forums, who didn't seem especially clued up).

The videos really are not very engaging (relative to any other course that I have completed here on Coursera). The concepts are not explained very thoroughly. Thanks anyway guys.

Too much content, so less practice. This course doesn't teach anything that you can make use of in the long term. It only gives an idea on what you have to work on in the future.

This is by far the worst course in the specialization. So many mistakes in the lab session, including unclear instruction, or syntax is not uniform across each module, and etc.

The artificial voice used over the video is truly awful for learning. I enjoyed the jupyter notebooks where I actually could learn what was bla-bla-blaed in the videos

The IBM Developer Skills Network (at labs.cognitiveclass.ai) is very slow and doesn't work most of the time.

It doesn't allow to finish the course properly.

Content is thrown to the student with too much information and videos of only 3-4 minutes. Too much to absorb and too little to practice properly

Too many errors. Please renew the course asap for the future learners. These errers are distracting and make the learning experience less fun.

Model Development and Model Evaluation & Refinement Concepts are not explained properly neither in Videos nor in Lab!!Really disappointing :(

Concepts of the algorithms are unclear. In the notebooks as well, it is not in a flow. Very confusingg for a beginner to learn from this.

more hands on, project based/game based learning. Mindlessly watching videos and regurgitating code in the labs can not be the only way.

Not a great course. Sometimes it is too fast and the explanations are very short. More hands on exercises would have been more helpful.

There are plenty of mistakes in the videos and in the lab session as well. Hope you guys can clear out those.

This was a very challenging course. Some concepts were difficult to grasp and required additional research

Frustrating when the peer reviewer doesn't actually understand Python and deducts marks for correct code.

Leaned some, but not a whole lot of real-world application, I recommend people take Python courses more

Not enough hands on problems, including variety and volume. Expected more from an IBM program.

Don't spend your money on IBM Data Science Cert. Course labs are full of bugs and not working.

coursework was easy but that damn final assignment was absolute hell for no reason whatsoever

Suddenly introduced complex codes and statistical functions. Videos were way too fast.

moderators do not respond to questions raised in forum. leading to incomplete learning

W​orst course in the IBM Data Analyst Professional Certificate. Very badly explained.

i​t was too fast and I didn't understand a lot of things