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.
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Habilidades en redes de IBMAcerca de este Curso
878.531 vistas recientes
Resultados profesionales del estudiante
14%
comenzó una nueva carrera después de completar estos cursos
18%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel principiante
Aprox. 20 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish), Persa
Qué aprenderás
Describe the languages, tools, and data used by data scientists, including IBM tools focused on data science.
Describe the features of Jupyter Notebook and RStudio IDE that make them popular for data science projects.
Create and manage source code for data science in GitHub.
Explain how IBM Watson Studio and other IBM data science tools can be used by data scientists.
Habilidades que obtendrás
- Data Science
- Github
- Python Programming
- Jupyter notebooks
- Rstudio
Resultados profesionales del estudiante
14%
comenzó una nueva carrera después de completar estos cursos
18%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel principiante
Aprox. 20 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish), Persa
ofrecido por
Habilidades en redes de IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Programa - Qué aprenderás en este curso
3 horas para completar
Data Scientist's Toolkit
In this module, you will get an overview of the programming languages commonly used, including Python, R, Scala, and SQL. You’ll be introduced to the open source and commercial data science tools available. You’ll also learn about the packages, APIs, data sets and models frequently used by Data Scientists.
3 horas para completar
17 videos (Total 84 minutos)
10 horas para completar
Open Source Tools
In this module, you will learn about three popular tools used in data science: GitHub, Jupyter Notebooks, and RStudio IDE. You will become familiar with the features of each tool, and what makes these tools so popular among data scientists today.
10 horas para completar
12 videos (Total 54 minutos)
5 horas para completar
IBM Tools for Data Science
In this module, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio. You'll learn about some of the features and capabilities of what data scientists use in the industry. You’ll also learn about other IBM tools used to support data science projects, such as IBM Watson Knowledge Catalog, Data Refinery, and the SPSS Modeler.
5 horas para completar
15 videos (Total 72 minutos)
2 horas para completar
Final Assignment: Create and Share Your Jupyter Notebook
In this module, you will demonstrate your skills by creating and configuring a Jupyter Notebook. As part of your grade for this course, you will share your Jupyter Notebook with your peers for review.
2 horas para completar
1 lectura
Reseñas
- 5 stars67,06 %
- 4 stars22,24 %
- 3 stars6,63 %
- 2 stars2,13 %
- 1 star1,91 %
Principales reseñas sobre TOOLS FOR DATA SCIENCE
por RR24 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!!!!
por FC5 de nov. de 2019
It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.
por YK24 de mar. de 2020
There was a problem with the connection to R lab, never fixed. Also, some tutorials are outdated. These are the negative parts and why I give four stars. Other than that I like the course so far.
por RJ7 de oct. de 2021
Great course with practical approach to tools that come handy beside data science with python such as git and github, Some basic R coding and a great introduction to IBM Watson studio and cloud.
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