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.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
- 5 stars69.40%
- 4 stars23.30%
- 3 stars5.29%
- 2 stars1.08%
- 1 star0.90%
This course is very educative and easy to follow by anyone regardless of their previous knowledge in Data Science. I recommend this course to anyone who want to learn r programming and data science.
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.
A good basic class and collection of the tools. I wish there had been a little more explanation of what we would use the software for, but I found the lecture parts to be both concise and informative.
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.