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.
Об этом курсе
Карьерные результаты учащихся
Прибл. 11 часа на выполнение
Карьерные результаты учащихся
Прибл. 11 часа на выполнение
Университет Джонса Хопкинса
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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Лучшие отзывы о курсе НАБОР ИНСТРУМЕНТАЛЬНЫХ СРЕДСТВ ДЛЯ СПЕЦИАЛИСТОВ ПО ОБРАБОТКЕ ДАННЫХ
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.
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.
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.
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.
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.
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.
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.
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
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
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.
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
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.
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 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.
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.
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.
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.
Well basically tutors only providing slides, speech, forums and ebook in this course...rest is self-learning, self-understanding, self-asking... if not, then you'll not pass this course i think..
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Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
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