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Learner Reviews & Feedback for Tools for Data Science by IBM

24,131 ratings
3,841 reviews

About the Course

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, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. 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 Skills Network 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 Watson Studio and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews


Apr 12, 2020

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.


Sep 15, 2020

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.

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3351 - 3375 of 3,850 Reviews for Tools for Data Science

By Scott O

Feb 23, 2022

G​ood introduction to programming languages and useful development environments. However, the IBM Watson section felt like a long commercial for IBM products. That section makes you jump through a number of hoops to register for IBM Cloud, a service that requires a credit card to even register if you don't follow the free trial instructions that are only given after the video lesson telling you to sign up. If you follow the video instructions you can lock yourself out of getting a free trial because your email can only be assigned to one account. IBM/Coursera's advice if this happens is "use another email address". Beyond that the instructions for completing exercises using that tool are out of date and not generally correct. This one section was enough to almost make quit this whole course, really disappointing.

By Karen P

May 23, 2019

There are lots of technical glitches in this one. Quizzes in a video before you've gotten to that information, missing links, places that ask your thoughts on something that really doesn't need thoughts, etc. I think it's also misplaced in the series. It assumes that you know a lot more about data science than you do if you've just watched "What is Data Science?" They talk about some great resources for writing in Python, R and Scala, but you haven't yet learned them if you take this as the second class in the series. I think there's probably a lot I didn't pick up on, simply because I didn't have the base that knowledge needed to build on. It might be a great class (if they fixed the glitches), if placed elsewhere in the series.

By Mark V

May 26, 2021

I did not enjoy my time taking this course. There is simply TOO MUCH information, and it rarely gets expounded upon. I often felt like I was just getting information dumped on me, such as listing the various Python or R packages we MIGHT use one day. Additionally, videos would often use data sets as examples but would fail to explain their context and don't seem to provide the data sets to work with on our own. This wasn't the case for the entire course. I enjoyed Week 3 where we spent a significant amount of time on one thing, such as jupyter notebooks or github. Instead of being told how something worked, we were able to play with these tools ourselves, and as a result I feel that I learned SO much more.

By Yousef K

Dec 25, 2020

This course leaves you doubting whether you can become a data scientist rather than providing you with brief knowledge on data science tools. I think it needs quite a bit of restructuring because concepts are explained in videos as if they are being explained to computer scientists and engineers rather than newcomers to the world of data science. Nevertheless, I'm glad I was able to get through it and move on to other courses in the certification that actually matter. My advice for you: don't worry about the complexity of the material and don't waste your time trying to understand the details because it's simply not worth it. Just get a grasp of the essentials and move on.

By Aaron A

Sep 2, 2020

A good overview of tools that are common to the field. The videos are just plain horrible. The narrator does not explain anything that he is typing on the screen, he makes frequent mistakes, and parts of the screen are not even visible. One video shot showed the narrator recording the video from the driver's seat of his car! Quality needs more focus. Also, the explanation of some of the labs are confusing and many many many students encountering similar errors...but when looking at that discussion forum, staff just cut-and-paste same unhelpful message to everyone. I guess you either figured it all out and make it through the course, or give up in frustration.

By Jay Y K

Nov 3, 2021

Part for Git was really great. It has provided me good overview what it is and how I'm supposed to leverage it at basic level, so it was very useful. Part about Jupyter Note was also good, part for R was alright, mainly because I'm not much interested in R anymore. But then too much time has to be spent for IBM tools. I understand that these courses are constructed by IBM and they would like to leverage it to advertise their tools. However, from learners perspective (presumably most of us are just beginner in this field), IBM tool part was just an overkill, way too much. I probably will prefer those courses provided by universities more moving forward.

By princess.ogbechie

Jan 12, 2022

It was interesting at the beginning but along the way it became uninterestingly long and monotonous. Though the part explaining the IBM opening part was hard to follow as my free trial had expired and there were no more claim codes for the extended trial. Most of the reference points and labs were from outdated versions. So they didn't load as expected. I experienced multiple error messages while trying to open the IBM cloud account and navigating to the Jupyter notebooks. The IBM page was also glitchy. I was not able to get access to the extended trial claim code so I had to open a new account to do the lab works and exercises.

By Polychronis ( P

Oct 20, 2018

Outdated lectures and low quality videos. Owful monotonous narration (puts you to sleep). It is as if IBM & Coursera are trying on purpose to put people off Data Science. :-)

The 1st course of this specialisation (What is Data Science) was truly educational, fun and easy to watch thus to understand and remember what you have learned. This course is the opposite.

IBM & Coursera people, the fact that someone is a super duper scientist doesn't automatically qualify to be a teacher nor a narrator, and please IBM, do improve the quality of the videos with better graphics and enriched material. We know that you can afford to do so.

By Daniel A

Jul 29, 2020

The first course in the IBM Data Science Professional track was excellent. This one is not.

This particular course is dry compared to the previous one. It’s difficult to pay attention when many of the videos are a boring presentation of dozens of data science tools. Week two is less dry but is poorly organized and needs more explanation and refinement (poor audio quality, lacking descriptions). There are also videos which are essentially repeats (cover the same information) of the previous course but of worse quality. Overall, this course lacks refinement and organization, and is not worth paying for.

By Jose A C

Apr 29, 2020

The content is a good intro into the tools that you are gonna use in a data career. However, I did have two major issues here where:

1) As IBM moved to Watson Studio from Data Science Experience, this did create some of the visuals and knowledge a bit outdated.

2) There was a massive disconnect when you have issues working Watson; especially with signing up and logging in. I see that this was a huge issue since then (judging by reading the discussion sections of the course) and this (along with my first point0 should definitely be discussed if you want this content to still provided.

By Monserrat R

Jul 23, 2020

It is a very quickly course, the week of the open source tools it's seen really quick, you can barely understand anything and they put three different tools in one week, if you really want to learn them search another course; it is also a big propaganda for de IBM tools, and they put so much more effort on selling you the idea that their products are really necessary that in actually introduce you to the tools that a data scientist use, and its so hard to understand if you don't speak english as your mother language, hope that with time they can fix it.

By Jay J

Sep 5, 2019

This course is not good. It has taken me several times the amount of time specified due to the outdated videos that no longer represent the tool as provided. Struggling to get simple markdown commands to work in the notebook, but I successfully executed them in the previous toolset. Several back and forth's between the actual work and the videos is very aggravating. It would be nice if you at least provided some printable instructions. I feel that I have gotten off track and may not be able to find my way back to a normalized starting point.

By Rachel M

Mar 2, 2021

Very patchy. Some of the videos were quite informative but the practical exercises were a real problem. Often the instructions were impossible to follow as the software must be a newer version than that shown in the instructions. I had to Google for the latest instructions. Also the practical exercises rarely told you *why* you were learning anything; it said "type in this code" but you didn't understand the code. I was able to finish the course but only through sheer perseverance (and Googling for instructions) - it was not enjoyable.

By Shawn G

Apr 7, 2020

This course at one time would have been great. However, for myself and many others (based on numerous discussion posts during my time taking the course), there was a multitude of technical errors and outdated training. Zeppelin Notebooks was not a working functionality in the IBM Skills Network, and most of the walkthrough guides were unhelpful due to updates in the tools being showcased. The course is in need of some serious updating to catch up on many changes that have impacted the tools covered in this course.

By TPereira

May 13, 2020

Material in this course looked like part of something else. It's a beginner's course but suddently I'm faced with a lot of technical jargon with no explanation. I supposed to experiment with software and code I've never seen or know how to interpret and I'm just suppose to run it to see what happens. I have no idea what I was supposed to learn from it. Week 2 was demotivating and added nothing to my knowledge. This week was an absolute loss of time. I still learned something from week 1 and 3

By Gus D

Apr 16, 2021

give one plus star with benefits of the doubt. If the course gets better in next courses but this is a shame. I can deal you promote IBM services and products, no matter with that, but you only give ALL the tools existing in the data science world and meanings, but with no knowledge is a none sense. Hope you improve, Basic stuff for analytics, statical or regression models, clustering I have no clue what they are. But well the name is tools for data science. No how to use them or what for.

By Shashank R B

Mar 11, 2019

The course needs to be updated. Especially the IBM Watson Studio section is something which needs to be worked on again. The site they refer to has hanged completely. IBM site was not user friendly and caused a lot of confusion. It took a lot of time to figure it out. This problem is not isolated and there have been a lot of users who are struggling to figure out how to solve it. This causes additional problems as the final assignment depends on getting started with the IBM website.


Dec 29, 2021

A lot of contents are not accurate since IBM website has been changed . And the final exam was terrible. For example, one answer was like Both A and B and there were no indication for A and B. Another question:What type of model would you use if you wanted to find the relationship between dependent and independent variables? If you choose regression model, it's wrong. If you choose Classification model, wrong again. Do I suppose to choose the wrong answer to get 100% grade?

By Jennifer S

Jul 30, 2019

Overall intro for open source tools that could be four stars if updated for current layout and usage of its star tool, IBM Watson. The inaccurate videos for Watson make this course very frustrating, and moreso because the final, graded project is expected to be completed on Watson despite the course's acknowledgement that the lectures need updating for that tool. It's doable, thanks to the other students posting tips in the discussion forums.

By Davy D

Mar 17, 2020

5 stars for the first two weeks, but the week about Watson is just terrible. The discussion board is full of complaints.

IBM should not promote itself this way.

Coursera should not spread this content and charge for it. It's a rip off.

The videos are totally outdated and it took literally hours and looking on the discussions on how to get to the point that I could do the application and the final assessment. IBM wasted my valuable time here.

By Ansel N

Mar 18, 2020

I am personally found it very difficult to create a notebook on IBM Watson because course take the tutorial videos from IBM Watson itself without checking whether there is any updates where the UX changed significantly. I have to research Google and forums to find out the ways to create a notebook on IBM Watson. I hope that this review will help the authors of the course find it easier to update the course content.

By Maulik M

Apr 7, 2021

Too much lip service to too many tools. After the first course in the specialization sets expectation that no tech or programming skills are essential as pre-requisites, this course comes along and introduces in the briefest possible way a plethora of tools.

The course will benefit by focusing on only IBM tools and one example from the open source world rather than the mention of so many tools all around the place.

By silvercodeify

Mar 11, 2022

Far too much focus on the proprietary IBM tools - in places the course felt like an advertising event to me. I had hoped that this course would provide a better overview of the many tools, but unfortunately other tools were only mentioned once at most. If this course was not part of the "Data Science" course, I would have dropped it. But I hope that the following courses will be more general again.

By Douglas M

Oct 3, 2018

Well structured layout and solid indications of what the knowledge necessary for a learning path to data science. Which is appreciated as there is a lot information out there and difficult to filter out the noise. The course however is very light and lacks some real educational information. The content would need to be 'beefed' up considerably. And more rigorous quizzes and questions needed.

By Vaughn C

Aug 15, 2020

A lot of good information here which should have been rated higher, but everything took so much longer than it ought to have, because it was so poorly presented. The materials are outdated (or missing/difficult to find with the IRIS dataset) and difficult to follow. The course needs a complete update and overhaul by someone who understands online learning and user interface/user experience.