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. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
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About this Course
Learner Career Outcomes
46%
45%
19%
Learner Career Outcomes
46%
45%
19%
100% 온라인
유동적 마감일
초급 단계
완료하는 데 약 7시간 필요
영어
강의 계획 - 이 강좌에서 배울 내용
Introducing Skills Network Labs
This week, you will get an overview of the various data science tools available to you, hosted on Skills Network Labs. You will create an account and start exploring some of the features.
Jupyter Notebooks
This week, you will learn about a popular data science tool, Jupyter Notebooks, its features, and why they are so popular among data scientists today.
Apache Zeppelin Notebooks
This week, you will learn about Apache Zeppelin Notebooks, its feature, and how they are different from Jupyter Notebooks.
RStudio IDE
This week, you will learn about a popular data science tool used by R programmers. You'll learn about the user interface and how to use its various features.
IBM Watson Studio
This week, you will learn about an enterprise-ready data science platform by IBM, called Watson Studio (formerley known as Data Science Experience). You'll learn about some of the features and capabilities of what data scientists use in the industry.
Project: Create and share a Jupyter Notebook
Open Source tools for Data Science의 최상위 리뷰
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!!!!
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.
제공자:
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.
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