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
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 9시간 필요
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 9시간 필요
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.
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THE DATA SCIENTIST’S TOOLBOX의 최상위 리뷰
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.
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.
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.
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's a very introductory course and in a sense I don't feel like I learnt something useful, except the part that shows how to install all the tools that are needed for the rest of the Specialization.
Consistent yet very basic course. I would only recommend this course if you are willing to complete the whole Data Science specialization or if you have troubles with the basic functioning of GitHub.
Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.
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!
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.
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
Pretty easy, and never felt like it was a struggle to find the information that was needed. Basically a setup course for out things you'll need for the likes of R Programming and Data Science work.
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.
Good introductory course. Gives you an insight into the courses and topics which you will come across in the future. Would recommend this for beginners who want to get an insight into data science.
Most of the instructions were very clear. Image quality for pushing files to Github via command lines was poor, so it was difficult to follow along. Not sure why there were 2 Git bash counsels open
It would be helpful for absolute beginners who even have difficulty in installing programs like R and GitHub but otherwise it felt a bit too basic although informative with some of the Git commands
Some of the course material seems a little out of order, and some things I went externally to figure out, but overall I think that it is a great class for someone looking to get into data science.
A very short (could be completed in a day) course to get you started on the rest of the Specialization. You will learn very basics of installing R and playing around with GitHub. That's it really.
Having to skip through all the Mac videos is annoying. Just make an option at the beginning if you're working on mac or pc or both so i don't have to deal with skipping some videos and not others.
A great introduction to some of the tools of a Data Scientist. Just enough information to get you going, but still leaves enough mystery so that some investigating and problem solving is required.
This course seemed a little to basic. I know it gets much harder going forward (as I've already started on the next course), but I feel like more knowledge could have been packed into this course.
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