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
Very clear and concise and is very easy to follow for those who aren't very experienced with setting up a dev environment or git. A little on the easy side but I'm sure more challenges are to follow!
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.
This course spoon-fed me as a beginner, which was great. The quizzes were well-done because they brought to light any weakness or gaps in my understanding so I could go back and review the processes.
Great course content and very much informative with the different options of learning either through text or video. A good introductory course to the Data Science: Foundations Using R Specialization.
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