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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,175 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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2651 - 2675 of 4,596 Reviews for Tools for Data Science

By Pradnyapal M

Mar 5, 2020

Its very good to know about the industry tools in the data scientist field where we use multiple languages using in one studio to integrate the programming .

By NaturallyMe D

Nov 28, 2023

New to Data Science, it started out a bit intimating. The instructions made it easy to follow. Excited to have completed the course with limited set backs.

By Charles J

Mar 27, 2020

Actually videos about IBM Watson Studio just describes the former edition instead of present one, so it can be really confused to practice as in the videos.

By Rafale C

May 20, 2019

Course material didn't update for IBM Watson Studio, makes learner spent super huge time to check the difference between material tutorial and real website.

By Matheus C M

Dec 12, 2022

Good introduction, but a lot of information that seems not important and/or applicable at this moment. It will probably be revised in other future moments.

By srustisuman m

May 31, 2019

overall very informative, loved it. just a suggestion, please renew the IBM watson videos because they are quite old and different from new interface there

By Adil W

May 24, 2019

Some online tools provided for course where not working properly, many times they failed to open and Rstudio in IBM Watson Studio failed to install library

By Madhavendra S N

Nov 20, 2023

Nice Course, the certificate seems to have ome worh but the material is pretty simple,maybe because i have already made some projects with help of youtube

By Anurag P

Sep 5, 2020

A great way to learn Jupyter Notebook fundamentals if you are new to it! IBM Watson suite is bit rushed but I believe that's the way it is supposed to be.

By Alireza M

Jun 9, 2022

It was a well managed course, Although it would be better to give me a choice whether I want to do the excercises in platforms other than Watson Studio.

By MANTRIPRAGADA K C

Aug 10, 2020

After completing the course, I got an idea on the tools that are used in Data science and also the hands-on learning helped a lot in improving the skills

By Alix H P

Jun 8, 2020

Good review--I enjoyed coming up to speed quickly withe IDE for Jupyter notebook using Python. So much easier to debug code based on the "cell-structure"

By Mitchell C

Dec 15, 2019

The steps the video has you walk through and the actual platform are slightly different which can be confusing. Overall, great introduction to the tools.

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.