The course videos need updating. I, and other students, have wasted a lot of time trying to follow the out of date materials, not to mention the confusion and frustration that it creates. If the materials were kept up to date, I would have left a five-star review.

The R programming ungraded practice set needs more explanation of the codes and process, specially pertaining to plotting. It is difficult for a beginner to understand the pre given codes without proper explanation of what the plotting code is executing exactly.

too much seperated and shallow information about tools. may be good for someone who wants general ideas about tools, but just to sparse info in my opinion. maybe concentrate on one tool and guide to use it properly would be better. really hard to finish this one

First two weeks were to the point and good introductions to Jupyter Notebook and Zeppelin, but the third week tutorial on IBM Data Experience is so out of date as to be useless for being able to set up a new project and complete the assignment. Very frustrating.

Jupyter Notebook module was explained well however other tools like SPSS Modeler were a little difficult to understand for me. While explaining some of the examples in Watson Studio, it main objective / problem of the project wasn't explained in the beginning.

The first two weeks of the course are poorly explained and don't have regard for total beginners. It gets really disappointing in week 2 where the quality of the videos and the structure of the lecturer is really poor. However, weeks 3 and 4 things get better.

It's comprehensive enough, but should include more exercises for programming. I don't think it was necessarily the right decision to make this course come before programming, but it should accompany programming. It was alright with respect to content, however.

The videos and instructions on this class were terribly outdated. Despite the warning provided at the beginning that the videos were out of date, this is still unacceptable. It takes very little time to make a video of the quality and length in these courses.

you will learn about some of the tools you will need to use, but they really need to have someone proofread and test these courses. in many ways it felt very sloppy. random lines being repeated unnecessarily, poor rubrics for the peer graded assignments, etc

Terrible experience with the IBM Cloud platform. An account is needed in order to achieve the final assignment.

At first they deactivated my account without any reason. Then, due to an error on their side, I had to spent 2 days in order to create a new one.

This course has a good introduction to some online, open-source tools. It does not really discuss the drawbacks of these tools or their real use in industry. The test questions are detailed "gotcha" questions and not aimed at true comprehension of material.

Lots of videos are outdated as the tools (Both CognitiveLabs/Datascientist workbench AND IBM Watson Studio) have gone major updates and it was very difficult to follow the video tutorials. Unless the videos are updated, I cannot give a better rating than 3.

Production quality on the videos was not what I would expect for a professional qualification from a reputable company like IBM. Content was okay, but focused heavily on the IBM suite of services, making it feel more like an infomercial than a tutorial.

I was pretty disappointed with the weeks of this course. Not only it lacks 'on-hand' tutorials but the vagueness of video lectures, lack of instructions for beginners. A total downer for amateur beginners whose looking into the world of data science.

Some material needs to be updated. Even though it has been clarified at the beginning of the course, many things have changed and the videos and reality are different. The concept is the same of course but it causes confusion among students.

Thank you

A decent enough intro to some of the tools, specifically Jupyter notebooks. Week 1 just mentions a bunch of technologies without going into much detail. Week 3 is in my opinion a waste of time as it functions mainly as an infomercial of IBM services.

Some issues with lab instructions not lining up with current version of the IBM cloud platform. First sections just kinda listed heaps of tools in way too much detail - later weeks were helpful in their focus on one or few immediately useful tools.

Last part is not updated. The videos and notes are of the old version of IBM Watson, hence the interface of the thing is just about completely different from the one shown and taught about in the lecture. IBM should change the videos and notes ASAP.

Technical challenges given differences between what was presented and what was found for exercises. In some cases steps didn’t render student getting the required options to complete all aspects of the assignments and/or took a lot longer to finish.

Multiple creation of logins was confusing. A lot of time was spent figuring out the links. Changing the name from Data Experience to Watson Studio probably led to some of it. Hope you guys streamline the steps and videos to match with what shows up.

I feel that I could have benefit much more from coding more with Python or R. I feel that all I know is how to activate the tools, and run scripts that are already written. I would have liked more time to practice the tools, facing real questions.

The course does a good job of showing the some available free tools for data scientists. However, I still haven't the impression of having learned any data science yet, after two courses in this specialization. I hope the best is still to come.

it is good to know there is a lot of free tools out there but it is not very practical. in reality, you will most likely use one tool and excel in one language, having tons of tool in the box does not mean having the equivalent in your brain.

The course is OK, the problem is that IBM tools seem don't work every time. I had to open 3 accounts with different e-mails to get to work with Watson Data Studio. The videos explaining how it works are outdated and don't correspond anymore.

A lot of information is thrown at you at once and really isn't explained other than that they are tools for data science. It would be easier to follow along if other random facts about them that aren't related to their purpose was removed.