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.
About this Course
What 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
- R Programming
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
- 5 stars69.47%
- 4 stars23.24%
- 3 stars5.26%
- 2 stars1.09%
- 1 star0.91%
TOP REVIEWS FROM THE DATA SCIENTIST’S TOOLBOX
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
Yeah, the robot voice is annoying. There needs to be better instruction on getting R Markdown to work. I tried in vain and gave up on it after looking at multiple forums with my same issue. Oh well.
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
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.
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