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Tools for Data Science に戻る

IBM による Tools for Data Science の受講者のレビューおよびフィードバック



What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....



It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.


Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.


Tools for Data Science: 2201 - 2225 / 2,983 レビュー

by Yeh Y J


good technical guide but lack the context. For example, there is no explanation on why i need to convert to RDD, why would i want to move the paragraph around. There is no practical references that aid the understanding of the technical steps. This needs to improve especially for someone who has very little programming background who probably only heard of SQL, Python and R at this point in time. Scala, Jupyer, Zeppelin are all new.

by Diane A


i did learn how to do specific things but i found that there was not enough context. i.e. when would i use Jupyter? When would i use R? SOme concrete examples and exercises would have been helpful.

What was particularly unhelpful was the fact that the videos were out of sync with the tool so it took me ages to figure out what was wrong. The videos need to be updated!! i saw that i was not the only one who found this difficult.

by Abdulah H A


I think it would be better if the course focused on one online platform such as Skills New Labs rather than learning about multiple notebooks with multiple programming language with multiple work benches. It is to some extent confusing for someone with no prior experience in working with python, scala, or R. Nonetheless, this course has allowed me to understand more about available options which could be beneficial for experts.

by Ismayil J


Course provide brief overview of available tools used for Data Science. For awareness good, for getting working skills on any of them, no. At the end I get confusing feeling what to use in which situations, as if they all do the same thing. Possibly I would recommended to provide awareness bout all, but give in-depth practice, additional week, for one of the tools. It could be IBM's or Apache Zeppelin as more universal.

by Sahil V D


The course is too hectic. As I am coming from Mechanical Engineeering background, the words used in this course related to data science(and related software) went above my head. There should be some videos regarding the basics of the terminology related to IT WORLD( with practical example) in this course. Watching that Juypter notebook and other tools were so challenging as they were difficult to understand for me.

by Tyra J


I was really interested in the open source tools, but I feel like this would have been more easily retainable by taking a Python course first. Also the last week was all about marketing IBM Watson Studio as a superior DS tool but it's UX was super difficult to navigate. The video tutorials were outdated so I had to Google and eventually kept clicking until I found something as simple as opening up a new notebook.

by Kateryna C


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.

by Vladyslav M


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

by Jeremy G


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.

by Miranda C


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!

by Vladimir K


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.

by Christopher S


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.

by Mohamed A L


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.

by Marcelo C O


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.

by Baraa Z


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.

by Mauricio J F C


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.

by Robin C


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.

by 刘四维


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.

by Laureta A


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.

by Jingran Z


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.

by Mariano G


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.

by Ankur G


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.

by Gavin P


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???

by Shady S


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.