In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
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About this Course
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository
Skills you will gain
- Data Science
- Github
- R Programming
- Rstudio
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Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Data Science Fundamentals
R and RStudio
Version Control and GitHub
R Markdown, Scientific Thinking, and Big Data
Reviews
- 5 stars69.47%
- 4 stars23.24%
- 3 stars5.26%
- 2 stars1.09%
- 1 star0.91%
HIGHLIGHTS
TOP REVIEWS FROM THE DATA SCIENTIST’S TOOLBOX
Good Data Science Tools foundation course. You get your hands dirty a bit and you get to learn how to solve some issues with resources. Great practical experience on top of the knowledge additions.
It would be better if we can attempt the assignments even if we are not enrolled to the course. It would really help us to evaluate ourselves about the extent to which we have understood the concepts.
It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
I really don't know much about this stuff, I think the jury's still out on whether the last four weeks will be helpful in the future. We'll see how much I think I've learned at the end of the course
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