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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,168 ratings

About the Course

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. 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. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews

ED

Aug 14, 2022

I love the detailing of every aspect of this course. The Labs, the free subscriptions and free trials provided by IBM Skills Network, everything has been so amazing. Thank you Coursera, thank you IBM.

MO

Apr 17, 2023

the best course for the beginner who is going to start his data science journey. This course tells you all options like tools, libraries, programming languages, etc. Highly recommended for beginners.

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2426 - 2450 of 4,596 Reviews for Tools for Data Science

By Lance M W

Apr 28, 2022

This course provides some high level information, but it could do with some more actionable examples. There were times when - during the videos - it would have been nice to "follow along" with one's own Watson Studio session. But because the instructors were showing data on their own accounts, this was difficult/impossible to accomplish. I look forward to moving on to "meatier" classes.

By Rick G

Jul 31, 2019

Class is a bit confusing because you're signing up for different services and using them. In the first week or two, you use one service, then in the middle weeks use a different one, but in the final assignment, you're using a service that you signed up for in the beginning. Still, pretty cool to get an idea of the open source tools available. This can could be better structured.

By Jayan T

Oct 22, 2018

Gives an overall high level idea on Cognitive Lab tools, Jupyter Notebooks, Zeppelin Notebooks, R-Studio IDE and IBM Watson Studio. IBM Watson section is problem prone due to product update and the same not reflecting in course contents. Also I had to wait for peer review since I could not find other candidates who have completed the course with me...Recommended for beginner level

By Yuanyuan T

Aug 24, 2020

Overall, this is a good course for the intro to data science series. It exposes us to many useful data science tools. However, I think since this course covers a lot of different tools, some questions in the quizzes seem too overwhelming. I suppose students usually forget what they learned because the questions are not actually helping them understand a practical problem further.

By Varun J

May 6, 2020

I enjoyed doing this course , i get to know about basics of various open source data science tools and had a great learning experience by hands-on-experience simultaneously. But there are certain topics which are not very clearly described especially for someone who is new to data science field so i do suggest more elaborated content inclusion that will be really appreciated.

By Musaini R

Apr 6, 2020

Overall, it is good. The final assignment managed to consolidate everything that we have learned. However, I think the R-Studio material definitely need a lot of improvement. I barely kept my eyes open, the instructor speaks in a non-engaging way, maybe, it becomes very 'dry' because the student cannot clearly sees what he refers to (the screen so small with white pointer)

By Noah M

Apr 19, 2021

I think there is plenty of value in this course, but it's hard not to be aware that it feels like IBM discovered "inbound marketing" and realized this platform is the best home for their style of campaigning.

I think the strongest aspect is the introduction of time-saving tools that could certainly enhance your workflow; that is, if you aren't already familiar.

By Pranay C

May 26, 2019

Slightly IBM oriented. Mainly focuses on Jupyter Notebook and Watson Studio on the IBM cloud platform. These two tools are extensively used throughout the courses in the specialization. Since this talks about "open source tools", I was quickly able to find the source code of Jupyter Notebook. However, I was not able to find the source code for Watson Studio.

By Aditya A

Sep 5, 2019

Course was great., good content!

However I was incorrectly graded in the final assignment hence weighing down my aggregate score. Though it didn't affect my much, it might have affected someone who had correctly answered but was wrongly marked by the grader whose understanding was not clear themselves.

Please have a look at the peer-graded evaluation system.

By Jukka H

Mar 4, 2024

Some of the course content was not really valuable on a theoretical level. For example: just listing Python or R libraries and then asking which library does what in the test assignment tested more the memory of participants rather than actual skills or understanding. Without proper hands-on experience, this kind of theoretical knowledge is quite useless.

By Vera G

Feb 23, 2020

Good as one can expect from Coursera.

However, one comment: the tutorials are based on an old version of IBM Cloud: version 2 if I remember well, when now it is version 3.6. So the pages are slightly different, and it makes it sometimes confusing to understand where to navigate for a student who was a beginner - which was the course's targeted audience.

By Shada A

Nov 7, 2019

at first i found it hard to relate to real life examples and the applications of the tools then after the peer garded assignment and working on the exercise following the steps that were so clearly explained and reading and understanding the Markdown Cheat Sheet, things got clearer and more interesting.

Looking forward to learning more about the subject

By Sisir K

Jan 11, 2019

Very informative yet easy to follow. One minor gripe I had with the course is that the tutorials for IBM Watson Studio (in week 3) were outdated, and the menus shown in the tutorial videos were absent on the actual Watson Studio website. As a result, it took some additional figuring out to perform some actions that were being explained in the video.

By Fab T

Nov 2, 2018

Well, very good course. The problem not to give 5 stars is that you show a lot of tools and no comment exercises to develop our skills. The videos are great, and the last project also's great, but only show the tools is not a great thing for the future Data scientist. So, next time, put some activities or commented examples, like the last project.

By M. S P

May 8, 2019

It starts from very basics so that very easy to understand and apply. However, education materials in videos are not updated so it makes difficult to find out where to an account create a notebook. For promo code, screens are totally different. I cannot find where to apply for it on the current version of IBM DSX. Hope, It will be updated asap.

By Shailesh k T

Dec 25, 2019

It was great learning in this course.This course was introduction to tools being used by data scientist.From various discussion threads and my experience in this course, I observed that coursera should update the videos specially for Data science experience.Bcoz lots of students are facing issues on low level works like creating notebooks...

By Sudhanshu M

Jul 22, 2019

I found several concept very unclear in this course, for e.g. asking us to see a sample notebook,article from IBM community and follow it from start to end. As a beginner to coding and data science this wasn't very helpful as I couldn't understand the concepts. A beginner level tutorial or code present for that would have been very helpful.

By Anmol G

Jan 31, 2021

honestly, it was well taught. but the key problem was that the videos by mr. romeo kienzler were a bit advanced for my understanding as i had no prior experience of this and i tried to replicate the the things he was doing and couldnt understand at all what im supposed to do ahead of somewhere. mostly this problem was in Github and Rstudio

By Robert B B J

Apr 25, 2020

This a great introduction to the three major open source use for Data Science. Don't expect too much. The individual tools discussed here is more of the high level usage and background of it and has some basic coding exercises. If you are looking for a more detailed course for one of the specific tool, you should find and invest for that.

By Andy G

Mar 23, 2020

Only issue we ran into is that there have been some URL and naming updates that aren't reflected in the training yet. Such as DSX is now call Watson Studio. The data science work bench also does not include Rstudio at the time of me writing this. I believe they are in the process of an update that is why the link to RStudio did not work.

By Tarun M

Jun 1, 2019

The course is structured well to get introduced to various open source tools. A minor issue is that markdown cell commands(such as Tables) for Jupyter notebooks as explained in introductory lessons does not generate results as expected. This leads to confusion, as a learner I am not sure if have followed steps correctly or its errata.

By Eric H

Nov 22, 2022

Good overview. However, the lab instructions have not kept up with the evolution of the applications used. For example, Watson Studio has changed its UI making it hard to follow the lab instructions that are based on a previous version of Watson Studio. Also, I had trouble linking out to Jupyter Notebooks from the Coursera page.

By BALARAM R E

Apr 17, 2020

This is course is for the beginners to the data science and have no idea of online open source notebooks like jupyter notebooks etc

It's a good course and introduces all the data science open source tools u would need to build a real time model.

Don't miss any part ,go through every part.

It was fun learning !

happy learning :)

By Srikanth S

Sep 19, 2019

Had difficulty with creating account on IBM Watson studio and getting the lab to work correctly. Instructors were responding to newly created questions and not to responses. I had to figure it out myself to finish the course and I am sure lot of other students are struggling as well. Please improve to make this course get 5 *.