It feels superficial, and I felt lost trying to do the assignments, as if I didn't have enough information to use the notebooks. I did a lot of outside Googling. If the purpose of the course was just to give a glimpse of what Data Scientists use, it did what it intended. But the experience was difficult, because I constantly felt I was expected to be able to do things that I hadn't been given the tools to do.

IBM Watson was updated and changed the design, it became harder to understand how create a notebook and etc.

IBM Watson is lagging, the code (Python 3.5) runs through time.

The final assignment is described incompetently, as there are bindings to the cells. In the beginning it is said that their number is varied, and then they give a binding of the context to them, because of which the evaluation is wrong

Course gives a broad overview of tools that are available for Data Science functions. However, I think it would be better to introduce more of this along the way particularly in the following Professional Certificate courses that focus on specific parts of Data Science. Its hard to connect the dots on what Tools are available when you don't really have the foundation yet on what you would use them for.

I learned a lot in this course but much of it was a result of the helpful comments of my fellow students. Sadly much of the material, especially the videos on IBM Watson, was out of date and useless. I was happy to be able to google terms and read the helpful comments from other students and find my way through the course, but this course is inadequate on its own and in desperate need of an update!

I wouldn't say it's good introduction to open source tools for data science. It's rather IBM open tools for data science. They highly recommend you to use this cloud based IBM tools but then you will face with a lot of problems with that - Skill Network Labs notebooks is impossible to use because it will kill kernel after minute or two of idleness; it will maintenance work in critical moments, etc.

The course has a lot of good material if you are learning about Data Science with no industry background. The hurdle to a better rating though is the outdated videos. They make the learning experience unnecessarily confusing when you are trying to apply the lessons in real world systems that have changed so drastically. With a few video updates, this would be a 5 star course for a beginner.

Too much information in a commercial format. I mean i get it that the course is offered by IBM, but a whole section presenting the different tools was maybe too much. The tutorials were not very informative and their pace was too fast. Also some vocabulary was casually used all along while never introduced at any point in the course so far. Really had trouble getting to the end of the course.

The videos are outdated and do not reflect the platform currently on IBM's website. I think that it would be easy to solve, but it seens that isn't the interest from IBM. I couldn't use the IBM Networks Labs because it had been offline for many days. The support is nonexitent. Nobody sees what's going on in the forum. Despite this, the course appears to be mor informative and a basic level.

Overall good but there were some dead links and ibm watson looks way different now than it does in the

lessons.It was hard to follow along because of the difference.I do understand that a data scientist is a problem solver so I took an extra 2 days to figure it out and in doing so developed some confidence in my ability.

For the price I would give it a 5 but this is an honest review.

In the end of the course (the IBM DSX section) there is a difference between what is presentated in video restructions and the real IBM cloud, it's called IBM watson studio, it went well for be but took a time (an hour) untile I've succeded to creat Jupyter notebook with the new updated clould, so I recommend you to keep updating the instruction videos according to the new updates.

In this course one can learn very useful tools, each of this with different targets, with good examples and material. But some material (mainly videos) are deprecated in some degree, turn learning in an uncomfortable experience, because lead to make some errors and many time must be invest in relate information of video with actual web tools.

I hope this problem will be solved soon.

This was a solid course. I learned what the tools were for data science. Some of the vocabulary was difficult though, as the instructor's seemed to expect that terms such as 'RDD' were common knowledge to the audience and did not stop to explain them. For me, it was difficult as I felt like I had to learn an entirely new language and then learn about the tools on top of that.

1.The interface was often "frozen", don't know it's the problem of the course or coursera.

2. The clips are too long-winded, explaining every single steps of creating accounts, projects, etc., which can be better done if we just explore them by ourselves. And the webs are already changed and operate differently compared to the clips, which makes the clips sort of misleading.

In really enjoying learning .However, I thing that the lectures must be updated to help to complete successfully our projects. Something valuable I learned from this course was click , delete .search make you feel comfortable with the new tools I learned. Hopefully , in the next courses we be able to get more clarification, especially iif we are new in data science.

I feel I just got to try a bunch of tools out there but didn't have a clue how they could be used in the real world. I mean I certainly could look into those tutorials in the community but registering for a course is to save me some time browsing through random topics. I think the course can be a bit more structured and provide more meaningful practice opportunities.

This course is well organized and rich in content; yet at times, it felt like instructors were just zooming though to deliver the content and not necessarily teach. Obviously they are not professional or trained teachers, but mostly it seems, they were just reading from the script, and that makes the experience and learning more challenging. Overall, great content.

A great course to get insights about various Data Science tools at our disposal to analyze and visualize data to make effective decisions. I thank the professors to make this course interesting and worth it.

Just one thing though, some more insights about these Data Science packages would have enhanced our familarity with these packages, thus helping us immensely.

Not good. Bugs. Discrepancies between material and tools. Probably needs to be updated. I might drop this track and go to another set of courses because this course is fundamental to the other 7 in this track, and IBM tools are not widely enough used to warrant spending a lot of time learning a track that is IBM tool specific.

And my latest submission is empty???

The outcomes expected from people in this course are vague. The course presents some more advanced programs within the modules and its not tole to us whether we need to understand the code or we are just supposed to run it as is without knowing what is happening inside. I mean the content is interesting but it is more advanced to beginner level.

A good course if you are interested to go beyond merely knowing what Data Science is and try yourself on the open source tools available.

The instruction in the course, however, can be a bit confusing, particularly if you do not have computing background. That being said, with a little bit of extra effort, a newbie can still follow this course.

Unfortunately, I did not have the best experience with this course. The IBM Watson Studio course content is not up to date. I spent a lot of time trying to figure out where to find information. Thankfully, the discussion forum helped me understand that the course content was a little outdated with regards to screenshots and nomenclature.

A great course to learn about different tools and to try writing code for the first time. But week 2 was not so great: some of the video's explained step by step what to do, but not why or what happened exactly. Some of the video's were the same as the readings and sometimes the order in which the metarial was presented puzzled me a bit.

A few instructions need to work on their communication skills and videos from week 2 have don't have a linear information flow. Plus, week 2 the instructors tend to jump into the middle of things which leaves the student confused.

All the other instructors and amazing and this course is a really good intro to many of IBM Watson tools :)

This one is basically IBM peddling its wares! But I guess if you don't already know how to use Jupyter notebooks, this can be a good place to start. I won't recommend paying exclusively for this course! But if you are taking this to get the IBM Professional certificate, then just go through it quickly with the videos at 2x speed.

The videos are not updated. I know the people in the texts say so but it was very difficult to me to follow one of them. Due to this, I realize how bad is Coursera's help and support and forum management since I had to find my way out to finish the course. This is a complaint on the platform, not on the course. The course is OK.