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
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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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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 stars69.45%
- 4 stars23.26%
- 3 stars5.27%
- 2 stars1.09%
- 1 star0.91%
HIGHLIGHTS
TOP REVIEWS FROM THE DATA SCIENTIST’S TOOLBOX
Great course for a beginner. But, since I knew most of the content from previous works, there was not much new learning for me. I am confident the later courses will enhance my knowledge a great deal.
This course is perfect for pure beginners, because it introduces the student to what Data Science really is and what a skills and knowledge a student should possess in order to be a Data Scientist.
It's a beginning to a host of different courses that are to be followed after this. It makes up a for a good platform to start off the work on R and how to use version control feature of R via GitHub.
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.
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