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, RStudio IDE, Apache Zeppelin and Data Science Experience. 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 Cognitive Class 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 Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
oferecido por
IBMInformações sobre o curso
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Resultados de carreira do aprendiz
36%
comecei uma nova carreira após concluir estes cursos
39%
consegui um benefício significativo de carreira com este curso
20%
recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
Aprox. 22 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
Resultados de carreira do aprendiz
36%
comecei uma nova carreira após concluir estes cursos
39%
consegui um benefício significativo de carreira com este curso
20%
recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
Aprox. 22 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
oferecido por
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Programa - O que você aprenderá com este curso
4 horas para concluir
Data Scientist's Toolkit
This week, 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.
4 horas para concluir
17 vídeos (Total 84 mín.)
17 videos
Languages of Data Science2min
Introduction to Python3min
Introduction to R Language3min
Introduction to SQL3min
Other Languages6min
Categories of Data Science Tools2min
Open Source Tools for Data Science - Part 17min
Open Source Tools for Data Science - Part 25min
Commercial Tools for Data Science5min
Cloud Based Tools for Data Science8min
Libraries for Data Science4min
Application Programming Interfaces (API)4min
Data Sets - Powering Data Science6min
Sharing Enterprise Data - Data Asset eXchange3min
Machine Learning Models7min
The Model Asset Exchange5min
4 exercícios práticos
Practice Quiz - Languages 30min
Practice Quiz - Tools30min
Practice Quiz - Packages, APIs, Data Sets, Models30min
Graded Quiz30min
12 horas para concluir
Open Source Tools
This week, 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.
12 horas para concluir
12 vídeos (Total 66 mín.)
12 videos
GitHub - Getting Started3min
GitHub - Working with Branches5min
Git and GitHub via command line (Optional)9min
Branching and merging via command line (Optional)5min
Contributing to repositories via pull request (Optional)8min
Getting Started with Jupyter Notebook5min
Getting Started with JupyterLab6min
Jupyter Architecture6min
What is RStudio IDE?4min
Installing Packages and Loading Libraries in RStudio IDE2min
Plotting Within RStudio IDE3min
4 exercícios práticos
Practice Quiz - GitHub30min
Practice Quiz - Jupyter Notebook30min
Practice Quiz - RStudio IDE30min
Graded Quiz30min
4 horas para concluir
IBM Tools for Data Science
This week, 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.
4 horas para concluir
15 vídeos (Total 72 mín.)
15 videos
Watson Studio Introduction4min
Creating an Account on IBM Watson Studio2min
Jupyter Notebook in Watson Studio - Part 1 2min
Jupyter Notebook in Watson Studio - Part 23min
Linking GitHub to Watson Studio2min
Other IBM Tools for Data Science1min
IBM Watson Knowledge Catalog6min
Data Refinery7min
SPSS Modeler Flows in Watson Studio6min
IBM SPSS Modeler7min
SPSS Statistics7min
Model Deployment with Watson Machine Learning4min
Auto AI in Watson Studio4min
IBM Watson OpenScale7min
3 exercícios práticos
Practice Quiz - Watson Studio30min
Practice Quiz - Other IBM Tools30min
Graded Quiz30min
3 horas para concluir
Final Assignment: Create and Share Your Jupyter Notebook
This week, 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.
3 horas para concluir
1 leitura
1 leituras
IBM Digital Badge2min
Avaliações
Principais avaliações do TOOLS FOR DATA SCIENCE
por CB1 de Nov de 2018
Tools are fantastic and will make a significant contribution to my education. Videos need to be updated for changes to Watson Studios. Support from IBM on their cloud services should also be improved.
por NK19 de Mai de 2019
The course video contents and the tools versions are not the same.There are some significant differences .Videos should be updated.In general the course is a good fundamental course about the tools.
por AJ15 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.
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!!!!
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