Chevron Left
Voltar para Tools for Data Science

Comentários e feedback de alunos de Tools for Data Science da instituição IBM

4.5
estrelas
22,480 classificações
3,522 avaliações

Sobre o curso

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....

Melhores avaliações

RR
24 de Abr de 2019

To the contrast of other reviews, I find the content very well bifurcated and fed to the learners. The course very easily digestable and I have had a great amount of fun learning it.. Go for it!!!!

AJ
15 de Set de 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.

Filtrar por:

176 — 200 de 3,521 Avaliações para o Tools for Data Science

por Sumanta S

10 de Ago de 2020

This course gives you an insight into the different tools available in different platform like Microsoft, Amazon and IBM , This course talks in details about IBM Watson and different services available. like Jupyter notebook and SPSS, data scale up others.

por Tebogo V A

10 de Jan de 2020

The course is amazing however the layout is a bit confusing especially with the platforms that were introduced on Watson studio. I feel like they need to introduce all the platform but choose one that will be used for the module. But overall it was awesome.

por Juan M H T

9 de Dez de 2020

Great quality content, it covers a wide selection of tools for Data Management, Integration and Transformation, Visualization, Model Building, Model Deployment and many more. It also gives extensive introduction to some of them with Hands-on activities.

por Heath W

27 de Mai de 2019

This is a great intro to a couple of the tools that one would need to be familiar with in order to be successful in Data Science. This area is going to require some extra work on the students' part to get familiar with the tools but is a great lead-in.

por Stephen M

23 de Mar de 2020

I enjoyed this course. The opportunity to work with Zeppelin notebooks, R, and Watson studio was great! The only small stumbling block was the old videos on Watson Studio. But you know about that and I'm sure you are actively working on it. Thank you.

por Carol L

30 de Jul de 2019

Este es un curso introductorio a las herramientas de analisis de datos, especialmente la de IBM. Me agradoó mucho porque se sentraron en la herramineta mas que en los lenguajes que se deberian manejar, los cuales serán abordados en los proximos cursos.

por Morgane B

21 de Jul de 2020

Ce cours est utile pour se familiariser rapidement avec un certain nombre d'outils data utilisés dans le monde à l'heure d'aujourd'hui. Les explications sont assez claires. Pour les labs et les devoirs, il faut juste suivre les consignes à la lettre.

por Pedro C G

4 de Dez de 2019

It is quite god to get to know the tools available

Recommendations, there are some changes to the current platforms, that information should be updated.

Question, why did we sign on to cognitive lab if the assignment will be completed in Watson Studio?

por VENKATESAN N

8 de Abr de 2020

It was awesome learning from coursera. Contents are well created to be understood by anyone easily. It's amazing and i wish everyone who is interested in data science should take up this course. Looking forward to take up more courses in course era

por Rodney C B

8 de Ago de 2019

Very good intro to the tools available.

The improvement to the training would be also how to do it in my own computer without connecting necessarily to an external tool and then once I'm ready use the tools IBM provide for a professional deployment.

por JAMES C

23 de Mar de 2019

I enjoyed this class. It gives good exposure to Jupyter and Zeppelin notebooks, as well as IBM Watson Studio. Students can spend extra time with these tools to get more depth of knowledge (but still introductory knowledge). Also includes some R.

por Bright O

29 de Out de 2019

The learning has been broken down step by step. This has helped me gained deeper understanding about RStudio, Zeppelin Notebook, Jupyter, Python 3 and more. Now I feel more encouraged to continue the course till the very end. Thank you Cousera.

por Christopher T Y E

28 de Jun de 2019

good intro to very very surface essentials of watson, zeppelin, jupyter, rstudio. though i didn't like the relatively extensive reading. video tutorials would be easier to follow cos a pic speaks a thousand words! but tqvm for this course!!!!

por Badal S

21 de Mai de 2020

It is an amazing course that helps us understand the basic tools required to be a Data scientist. The course was indeed insightful and I highly recommend the aspirers of data science or analytics to begin this course and have happy learning.

por HVictor

18 de Set de 2019

I've only had the chance to work with Jupyter notebooks as its what I had originally started learning with. This course allowed me to see other tools that are out there. Expanding my visibility into areas I had otherwise not been aware of.

por Priscilla S

27 de Abr de 2020

Great way to learn about the open source tools for data science to dive deeper. One suggestion would be to consider updating the IBM Watson Studio section videos. It appears that significant updates have been made to the website since 2018.

por Anette F

3 de Nov de 2018

Great introduction into Open Source Tools and into the basic workings of these tools. I love the labs, this is so hands-on and really gives the most realistic view on data science tasks and how they are done that I have come across so far.

por Kanishk K

11 de Ago de 2020

At the beginning, this course tries to overwhelm you with a lot of tools and you'd think IBM is just advertising but later in doing a simple project in this course you'd be thankful IBM provided all the tools in one place in the cloud.

por Neelabh S

28 de Mar de 2020

Really nice introductions to these amazing tools such as Jupyter Noteboos, Zeppelin, IBM Watson Studio and RStudio IDE. Very easy to grasp and the final project helps practice all the basics in Jupyter notebook using some Python code.

por Jafed E G

6 de Jul de 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

por Jason K

21 de Mai de 2019

Very good explanation of all tools that is available to users to enable them to work effectively. The labs also proved helpful with practicing and getting familiar in terms of navigation and getting use to the different environments.

por Mateusz K

1 de Jan de 2019

Nice review of existing open source tools and free to use web services implementing those tools. Personally I would also enjoy some introduction to either how to set up those open source tools on a personal computer or private cloud.

por Harry F

21 de Set de 2021

Excellent course to begin introduction to the most useful tools for data science from data compilation to model building process.

The videos and demos are very understoodn and show too many information about the data science tools.

por 053 V N

27 de Abr de 2020

this course I good enough to under stand which tools are applicable in data processing in data science . thanks Coursera for providing such a course that was very funy I enjoyed my valuable time learning with Coursera and faculty

por Suraj R G

3 de Dez de 2019

Fantastic course it was. I got overview of most of the open source tools for Data Science.

The Assignment at the end of the course was also interesting as it summarizes all the things we learned.

Thank you for such awesome content.