The Data Scientist's Toolbox
Data scientists are in high demand, and this course provides an introduction to the tools and ideas they need to succeed. Learn the basics of data analysis, version control, markdown, git, GitHub, R, and RStudio in this comprehensive course. Get the skills you need to become a data scientist and start your career today. ▼
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Course Feature
Cost:
Free
Provider:
Coursera
Certificate:
Paid Certification
Language:
English
Start Date:
3rd Jul, 2023
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [June 30th, 2023]
What skills and knowledge will you acquire during this course?
The course will provide an introduction to the main tools and concepts used in the data scientist's toolbox. It will cover the data, questions, and tools that data analysts and data scientists work with. The course has two components: a conceptual introduction to the process of turning data into actionable knowledge, and a practical introduction to specific tools such as version control, markdown, git, GitHub, R, and RStudio.
How does this course contribute to professional growth?
The course "The Data Scientist's Toolbox" contributes to professional growth by providing an introduction to the main tools and ideas in the data scientist's toolbox. It offers an overview of the data, questions, and tools that data analysts and data scientists work with. The course has two components. The first component is a conceptual introduction that helps understand how to turn data into actionable knowledge. The second component is a practical introduction to various tools such as version control, markdown, git, GitHub, R, and RStudio, which are commonly used in the field.
Is this course suitable for preparing further education?
The course "The Data Scientist's Toolbox" provides an introduction to the main tools and ideas in the data scientist's toolbox. It offers an overview of the data, questions, and tools that data analysts and data scientists work with. The course consists of two components. The first component is a conceptual introduction to the ideas behind turning data into actionable knowledge.
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