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Вернуться к Набор инструментальных средств для специалистов по обработке данных

Отзывы учащихся о курсе Набор инструментальных средств для специалистов по обработке данных от партнера Университет Джонса Хопкинса

Оценки: 32,989
Рецензии: 7,046

О курсе

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....
Основные моменты
Foundational tools

(рецензий: 243)

Introductory course

(рецензий: 1056)

Лучшие рецензии


7 сент. 2017 г.

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.


14 апр. 2020 г.

As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.

Фильтр по:

4801–4825 из 6,942 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Madhusudhan T

23 мар. 2018 г.

An interesting introduction to data science, Git and GitHub. Hope GitHub is explained in a little more detail. Quite a few people found a couple of problems with the final project. The community is great and there are people who will help. Looking forward to the next course!

автор: Tina L L

28 апр. 2017 г.

The course is great but there are some serious glitches happening in the Coursera platform that desperately need attention. I just went from showing that I did not pass the peer review section and in the next second was greeted by a big green Course Completion Certificate.

автор: anjali v

1 апр. 2018 г.

This course is a great introduction to what data science essentially is and all the necessary tools required to start your analysis. However, it would be great if the examples used in the videos were explained a bit more in context rather than being stated plainly.


автор: Zainul A

21 дек. 2017 г.

A little unclear about the process for using Git & Github. The common functions/code are thought, but I believe a demo or a video review for the last assignment should be shared. Other things in the course provide a good introductory insights to the world of Data Science.

автор: Tanmay B

23 мар. 2017 г.

It is a really nice course if you plan to complete all the 10 courses in the Data Science Specialization track. As a standalone, It is not that great a course as it basically introduces you to different things and you need to do other courses to actually learn something.

автор: William B B

7 мар. 2019 г.

This is an excellent basic course. The main problem I had was understanding the computer voice at times. There is also a quiz question or two that refer to commands in Studio that are not up to date, but only a couple that I found. All in all, it's an excellent course.

автор: Naveen K

26 нояб. 2016 г.

Great intro to Data Science Specialization. Hoping to complete the other courses as well. Dispels my myth about Data Science is all geeky stuff. Looking forward to bust more myths.

This course is light, broad and introductory. 4 weeks is a sweet spot. Keeps you engaged.

автор: Apolline M

23 окт. 2016 г.

Not much to learn, I would have liked a more thorough introduction to data science's principles.

Yet, everything is really presented step by step to make sure that all participants install correctly all tools needed for the further classes included in the specialization.

автор: Sally L

8 дек. 2020 г.

I did not know how to use R or R studio neither did I know what they entailed. With this course, I am now more aware. Being a solution provider. It is definitely a course you should check out to be conversant with the data scientist's tools especially R that is popular.

автор: Tony D C

6 апр. 2020 г.

This course is perfect to get an introduction to R and RStudio and the Github. It's easy to follow and pretty fast to complete. Probably the best thing you take home from this is to have a nice setup for the following courses where you can use the tools presented here.

автор: MHE v A

28 окт. 2020 г.

Very good, basic level course. Only one minor issue when working on the markup section, make sure to install TeX before you start, or R will not be able to generate a pdf. Not a major thing, but something that did frustrate me for 15 minutes while I got it all set up.

автор: Bernardo M F d S

9 мар. 2018 г.

Although I understand that Data Science involves a lot of self-oriented research, more resources and recommendations for learning git basics would be appreciated. Perhaps some practical exercises before the final assignment would've ensured a better learning process.

автор: Rok B

4 апр. 2019 г.

It is a good start to data science, you don't need a background in programming. The course is aimed at 1) helping you set up R, RStudio,git and conect it to GitHub and understand it's basic functionality and 2) getting a basic understanding of what data science is.

автор: Vamshi K P

12 нояб. 2020 г.

The course covered most of the necessary tools in the Data Science industry. The content is clear and very easy to retrace the steps. Git version control required a deeper explanation of undoing a commit, branching and merging. The rest of the content is flawless.

автор: REDROUTHU B S - C

18 июня 2020 г.

The track consists of 9 courses that each last about 4 weeks which are released in batches of 3 courses each month. This course introduces the very basics of R and R studio, Git and Github and a few otherthings that will be used in the data science specialization.

автор: Brandon T

16 нояб. 2017 г.

A little daunting at first but the instruction is simple and the ability to search video transcripts for tidbits basically saves me the step of taking notes. Some of the navigation was difficult in the forum, but I ended up figuring it out and posting something.

автор: Marcio R

9 авг. 2021 г.

Very helpful and important introduction to the world of Data Science. I do feel an overall lack of more examples and/or small optional projects/exercises to help learn, though. Maybe something like a list of exercises could be given at the end of each Module?

автор: Abdul-Mateen Q

22 нояб. 2020 г.

This course gave me a thorough introduction to the use of the tools in preparation for being a data scientist. I also had a good grasp of what task a data scientist faces on job. R, RStudio, Git and GitHub are nomore nightmare for me having taken this course.

автор: José D

11 окт. 2020 г.

it implies statistical concepts that, I understand because I have studied them deeply in my college, but for someone who has few or no knowledge about the subject, it can be very complicated. still its very complete and I learnt a lot about R studio program.

автор: 孙晓

21 февр. 2022 г.

The course is suitable for browsing in one day. There is not much deep knowledge, only some shallow concepts. I feel that as the beginning of a group of courses, the concept introduction is not too comprehensive, and many aspects have not been introduced yet

автор: Benjamin S

6 сент. 2017 г.

Good starter content, data science background and overview of tools. Could provide more lecture time on the tools (RStudio, Git/Bash). The course is labeled for beginners, but I can see where someone without much experience could really get intimidated by

автор: Ron C

9 июля 2021 г.

The course provided a good overview of Data Science and the various tools used to perform the work. Those without an IT background may find it challenging to install and configure some of the required tools. But you can find plenty of tutorials on YouTube.

автор: Vinayak N

1 авг. 2019 г.

Well structured and nicely organized. Content is great and lays the ground rules for start of statistics using R.

Minus one start only because there's no instructor teaching the course. I would've preferred a real human voice rather than an automated voice.

автор: Vishnu K

25 июня 2016 г.

The videos might not seem a lot at first view, but they contain links to some of the most useful material out there. The mentors on discussion boards are immensely helpful as well. For the uninitiated in data sciences, this is a great module to begin with.

автор: Steve S

8 мая 2016 г.

Good pace for the first course. A little more guidance on Git command flow would be help. However, the available Help documentation on Github did the trick. The problem was having to work primarily in the command line which provides limited feedback.