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Lots of videos are outdated as the tools (Both CognitiveLabs/Datascientist workbench AND IBM Watson Studio) have gone major updates and it was very difficult to follow the video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.

I found some of the lessons hard to follow. The web page has been updated but the class has not. I still enjoyed the class and learned some valuable information but it would be nice if the data being taught was current with the webpage.

The course is rich in information, but in my opinion it shouldn't be the 2nd course in the IBM Data Science Professional Certificate. It should come later when students are more familiar with the different steps of data science projects.

The course did not present didactics at the same level as others Coursera courses. The mix of IBM tools for training in the same space as the service sales environment makes learning confusing. The exercises on the tools were very basic.

Good introduction to multiple data science tools and their integration with one another .

The instructions in many of exercises are not explicit and in some cases not complete. There is a lot of room for improvement with the exercises.

First part of the course was great, learned about tools and stages of the data processing. The end was overwhelmingly focused on IBM tools, which even depended on an IBM account that no longer worked by the time I finished the course.

The instructor could do a better job clearly explaining the topic and/or material, showing a step-by-step 'how-to' on tasks, and testing on what he teaches. There were instances where the quiz questions were not covered by his videos.

In general the contents of the course are good, however, I thinkg that there's too much time waisted in promoting IBM products rather than actually teaching some more introductory things about all the tools mentioned in the course.

Hi,

while it was good learning about the tools and platforms that exist, I was a little confused by the IBM Watson Platform that did not function that well. That was not the best experience, so I hope the creators can address that !

a large amount of tools which I think are not that necessary has been packed in this course . So it make learning a bit confusing to the learners as which tools are the best . Please remove the extra material which isn't necessary

Good course to understand the tool set and learn basics. However, the site used in the course is now updated which made navigation very difficult. It would serve the student to update these videos and make the most of their time.