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.
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검토
2020년 9월 25일
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.
2019년 1월 31일
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.
수업에서
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.
강사:
Aije Egwaikhide
Senior Data Scientist
Svetlana Levitan
Senior Developer Advocate with IBM Center for Open Data and AI Technologies
Romeo Kienzler
Chief Data Scientist, Course Lead
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