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.
Auto AI in Watson Studio
å®”é
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!!!!
The course is interesting. It presents large spectrum of tools. It could be more helpful to provide general information on different tools and focus on few of them such as R, GitHub for example.
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. Youāll also learn about other IBM tools used to support data science projects, such as IBM Watson Knowledge Catalog, Data Refinery, and the SPSS Modeler.
ęå¦ę¹
Svetlana Levitan
Senior Developer Advocate with IBM Center for Open Data and AI Technologies
Romeo Kienzler
Chief Data Scientist, Course Lead
ę¢ē“¢ę们ēē®å½
å č“¹å å „å¹¶č·å¾äøŖę§åęØčćę“ę°åä¼ę ć
Coursera Footer
