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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
29,112 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

DE

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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2776 - 2800 of 4,751 Reviews for Tools for Data Science

By Kanchan P

Jan 10, 2019

Good hands on experience using jupyter notebook and open source tools! But the videos needs to be updated according to the new IBM watson studioplatform!

By Dam M

May 22, 2022

I think you need to update the assignments involving IBM Watson. The instructions were missing key instructions. Like "Save Version" instead of "Save".

By Naveen K

Nov 12, 2019

A Discussion on Data Science Tools that IBM provide for Free(need to upgrade for more Resources); Which are very much sufficent to complete this course.

By Diwakar P

May 27, 2019

This course offers a very good introduction to all the tools used by data scientists, along with explanations of the various features available therein.

By Fagner B

Sep 16, 2022

O curso é excelente, mas senti falta de mais exercícios práticos aprofundados. MAs super indico para quem está interessado na área de Ciência de Dados.

By neha b

Jul 5, 2022

Its benficial as helps in upgrading skills as gives hands on expericience through various lab work assignments on important tools used in data science.

By Abimbola A

Sep 10, 2020

The course kept me motivated to go on with my pursuit of becoming a data scientist. Still learning and waiting to see what other courses have to offer.

By Winnie C

May 22, 2020

The course is a basic introduction to a few data scientists tools, but not for practice. I Would like some project that could be written on the resume.

By Neelam S

Nov 14, 2019

Course syllabus is good and covers almost everything as mentioned. But the software tools are upgraded and that need to be updated in Instruction sets.

By Madhav

Feb 21, 2019

It's good course. Really helped to understand overall data science tool available . Hands on experience helped me to get a feel of how the tool works.

By Antonio C

Feb 8, 2021

Overall great course - sometimes lectures were not very refined; I liked the final assignment, which required to research commands on Jupyter Notebook

By Ilka D

Jul 9, 2020

Interesting overview with easy to understand practical examples on the one hand but also too many shallow descriptions of existing data science tools.

By Cornelis B

Mar 21, 2020

A good overview but the videos need to be updated to reflect the way the platforms look right now as they've been updated since the course was create.

By Lapaev M

Aug 21, 2019

Text information in videos about RStudio wasn't always in correspondence with thing were done on screen, and in my opinion it can be improved overall.

By Barış O

Dec 10, 2023

it have lots of information however this informations is not enough to learn the fundamental even the general knowladge. and everything is mixed here

By Gaadha J

Jan 19, 2021

I feel very excited to gain more knowledge. It become very interesting as I go through each course. Thank you Coursera for your support and guidance.

By Muhammad U A

Jul 13, 2020

It was overall a good course but it felt a bit outdated. I think it can be improved by including modern tools and not focusing so much on IBM Watson.

By Martín r

May 17, 2020

Good starting point into what Notebooks are, and what you can do with them. I only wish the assignments went more in depth into the tools and coding.

By Kris O

Mar 7, 2019

Good overview of tools that are used. Still basic information but starting to become more technical if you are apart of the IBM Data Science course.

By Imran R

Jan 6, 2019

Overall course was very short but it was good to know the basic knowledge of tools integrated with IBM Watson such as Notebook, RStudio, Spark.etc

By Sam S

Mar 1, 2022

A very good intro to the tools used in data science, good hand-on. The Data Refinery lesson could have been better explained, it was rushed thru.

By Cheung N L I

Sep 28, 2019

The course material is not up-to-date as IBM Watson Studio is updated, therefore, all the steps are not valid anymore. It is very hard to follow.

By Animesh K

Sep 14, 2019

This course is good but the tutorials for starting project in IBM Watson is outdated. Please upload latest tutorial as creating lots of confusion.

By Stella S M

Dec 26, 2018

Some instructions on setting up an IBM Watson were outdated; getting started info versus what was displayed on the interface did not always align.

By Remy E F

Aug 31, 2018

The IBM Data Science Experience videos need updating since its now IBM Watson. The interface is a bit different and I had to Google how to use it.