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 The hurdle to a better rating though is the outdated videos.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The videos are outdated and do not reflect the platform currently on IBM's website.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.

Too much information that you should remember while practicing and writing some code but authors think that you must learn it by heart and answer where each button is located. I think this course (like the previous one) could be twice shorter. But for the sake of justice I will say that practice parts with RStudio and Jupyter can be interesting for people whithout any technical background.

This felt very salesy, like I accidentally signed up for an IBM sales seminar or something and couldn't get out of it. Don't feel like I learned the tools very in depth either. It was more of "look at all these IBM products that exist! They're great!" It was just really in your face, and I think it could be more up front what this course really is, advertisement space paid for by IBM.

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.

Warning for those whose native language is NOT English:

These IBM Data Science courses are in DESPERATE need of review by a native English speaker. If English wasn't my first language, I can only imagine how much I would have struggled. It is pretty unbelievable that they expect people to pay money for courses that have so many many grammar, syntax, and audio transcription errors.

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.

The course provided an overview and very shallow hands on tutorials. appropriate for beginners. Course materials were out of date and IBM's own platform was not working as intended for the course causing frustration with this student and others as seen on the discussion board. Even so, I learned quite a bit on how to get started with a good sampling of tools.

Thank you.

Lots of material and tons to remember. It's unclear what is important and what is just "good to be aware of" until you get to the quizzes and need to remember much more in detail. The videos are way too fast for beginners inmy opinion but the exercises are well explained and easy enough to follow along. I would not recommend this for someone with no experience in this field.

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.

Please fix the Watson Studio and IBM Cloud access. Once the 30 free trial is over, it is extremely difficult and frustrating to get access again to complete the final assignment for the course. The final exam is much too difficult for a beginner course of this caliber. The information being tested was too detailed for a course teaching a tools overview for data science.

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???

Some good material on Jupyter and Github but way too much on IBM cloud/Watson.Also, most of the IBM materials were out of date with poor explanations requiring you to figure out how to do things in the cloud on your own, with trial and error. They also tested the IBM material through irrelevant minutiae making the quizzes harder than they needed to be.

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.