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Отзывы учащихся о курсе Tools for Data Science от партнера IBM Skills Network

4.5
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Оценки: 24,388

О курсе

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....

Лучшие рецензии

GC

12 апр. 2020 г.

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.

AJ

15 сент. 2020 г.

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.

Фильтр по:

251–275 из 3,915 отзывов о курсе Tools for Data Science

автор: Deleted A

24 июля 2020 г.

ONE CAN ACQUIRE BEAUTIFUL KNOWLEDGE TO THE TOOLS USED BY DATA SCIENCE COMMUNITY ALONG WITH APPLING THEIR SKILLS ON PRACTICAL ASSIGNMENTS AND PROJECTS ON THE USEFUL PLATFORMS ,

ITS WAS A NICE COURSE .

автор: Giulio C

13 апр. 2020 г.

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.

автор: LALIT K

30 авг. 2020 г.

This course is awsum and well explained. Some portions needs to be updated based on the current platforms. i.e Lab instructions should be inline with the current screen, e.g. Watson Studio.

Thanks !

автор: Mari-stella

1 мар. 2020 г.

Good to overview web-based data analyzing tools like Jupyter notebook, Zeppelin notebook and R studio IDE by getting access to virtual environments like Skills Network Labs and IBM Watson studio.

автор: Ahasanul H

18 апр. 2021 г.

All the tools required for ML kick starting was explained very clearly and it helped me a lot in building the understanding of what tools need to be learnt in the field of ML and Data Science.

автор: Juan C S G

4 июня 2021 г.

G​reat course! The course gives you a good overview about the tools and technologies of data science. The course also gives the opportunity to practice in the environments of the main tools.

автор: AckoGon

23 дек. 2020 г.

Provided an encompassing introduction to the variety of Open Source and Commercial tools available to conduct Data Science, and great interactive labs to get started working with those tools!

автор: Juan M C C S

20 авг. 2020 г.

Es un buen curso para esclarecer cuales son las herramientas que se deben dominar en la profesión. Funciona bien como introducción practica a calentar motores para ver que es lo que se viene.

автор: shiva k P

16 дек. 2019 г.

The videos in this course are outdated and the content in videos doesn't match with the reality because the videos are old and Watson studio got updated. Course content must be updated ASAP.

автор: Eugene V

18 сент. 2019 г.

Useful, quite a bit of practical. I've learned a lot of new tools and possibilities to use them for free; although based on IBM infrastructure, they're open source and may be used everywhere.

автор: Pablo M

4 июня 2019 г.

Does a good job of showing areas to obtain access to use Python, R, and Scala. You can however tell they're pushing IBM products when in reality there are many other options such as Anaconda.

автор: Sujit K

21 июня 2020 г.

I could learn how one can use IBM Watson in the entire Life cycle of Data Science and automate every mundane task which ultimately speeds up the Data Science workflow to a significant level.

автор: Orestis P

2 мая 2020 г.

very good structured and easy explained. most important: you can practice the basics of a (juoiter,zeppelin and RStudio IDE) lab while the instructor is giving an overview of the environment

автор: Harsh N M

18 дек. 2019 г.

Great course to gain knowledge from.One must spend a good amount of time in order to learn the basic tools of data science and thus won't find it difficult to work in data science in future.

автор: Tylar H

23 мая 2022 г.

Lots of great information. Seems to be an issue with accessing Watson and completing the last assignment. Instructors allow you to use a quick and easy fix by submitting it through GitHub!

автор: Todd J

19 сент. 2018 г.

Another Great class. Really introduces you to new tools that out there, not just for Data Scientist to use, but for anyone that has the use for R or Python coding etc. Loved the course.

автор: Fatih

13 апр. 2022 г.

It contains very useful information that can be learned on the way to be a giver. I learned many tools from creating a repository in git hub to writing a python topic in jupyter notebook.

автор: Daniel L

19 окт. 2019 г.

Impressed by those notebooks or development environment, and its availability on Web; very practical to document the method used in a data study, integrating programming with documenting.

автор: Samuel B

8 февр. 2021 г.

Passo a agradecer a todos os professores do Instituto da Educação pelos conhecimentos que me transmitiram e que foram importantes no desenrolar deste trabalho. Parabéns a IBM e Coursera.

автор: Joshy J

7 сент. 2019 г.

Good Course. Help you understand the most used open-source tools for Data Science. It also introduces IBM Watson Studio which is the best cloud-based collaborative tool for Data science.

автор: Thông T

29 апр. 2020 г.

Thank this course for letting me know there are online tools for data science, which help collaboration anytime and anywhere. It is trusted because it is from IBM, a well-known company.

автор: Berkay T

28 авг. 2019 г.

Brief introduction to what cloud platforms available to execute coding in different kernels. You also get an idea on how you will be analyzing data with what sort of tools and outcomes.

автор: Miduna K

26 авг. 2019 г.

Pretty nice introduction. A short course, don't expect anything too technical, but i think in a world of heavy and long MOOCs, its not a bad thing to start off with a lightweight one :)

автор: Thomas D

18 апр. 2022 г.

G​reat overview which included GitHub and other tools. The final module was much more than expected, where it updated with very useful tools on IBM Watson in relation to Data Science.

автор: Kunal J

18 окт. 2019 г.

Introduces us to some really nice tools and also IBM Watson cloud service which has a lot of resources and IBM doing a service to the community by providing you many of those for free.