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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: 33,077
Рецензии: 7,064

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.

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4751–4775 из 6,962 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Max M

16 февр. 2019 г.

I believe an updated version would be beneficial, as some R packages have now somewhat different functionalities. Furthermore, I would have liked a bit more instructions into how to create a markdown file. Otherwise fairly easy course; not sure what to expect for the rest of the specialization then, although I've read very positive results. Therefore, I will continue.

автор: Leandro A S

10 окт. 2017 г.

The material is good, the subject is interesting, the slides are ok, but the audio is suboptimal. In addition, there could be slightly more interaction (I mean the lecturer recording videos with him doing things at git bash, for example). This course is a simple and good preparation for the further courses on the Johns Hopkins Univerity Data Science track at Coursera.

автор: Sumit S

21 апр. 2020 г.

Really great content, but not a fan of automated videos (as of now). If booking a recording hall is a hassle, a background human voice with slides will be a much better option. If I were to complete a course just by reading study material, I could have chosen a Book instead of a MOOC.

Keeping this issue aside, Overall great content for getting started in Data Science.

автор: Dale O J

9 мар. 2018 г.

This is a good introduction to the tools necessary for Data Science. The lectures are comprehensive. Nevertheless, I view online tutorials for Git and GitHub as well as Dr. Leeks book The Elements of Data Analytic Style as being important supplements to the lectures to clarify and amplify the points that Dr. Leek is developing and attempting to impart to the student.

автор: Mateus S F

19 мая 2020 г.

Video-classes are presented by software voices (with an alternative of using only the text/slides provided by developers), which is a little bit annoying and distances the student from a motivating experience of having an actual professor, an example/model figure to be pursued. The content of the course is complete and well explained by the provided material though.


21 апр. 2020 г.

Course content was too great but that robotic voice i know its still in development but that voice always irritated me and made me distracted .Sometimes i got errors even though i followed the course content exactly the same way you did but it is good to correct the errors on myself.Thank you for this awesome course but i hope you come up with a good robotic voice

автор: Alessandro V

18 апр. 2020 г.

I appreciated a lot the program regarding the toolbox, many good references and links are included.

I found a little vague the definition of P-value. I can understand that this was included inside an introductory section, however the criticality of this definition shouldn't be neglected. (I posted a specific comment in the forum of week 4)

Thank you

Alessandro Vasta

автор: Fielding I

9 янв. 2021 г.

The parts that actually talk about data science are great. Polly's voice isn't too bad, almost gives everything an "I am MOTHER" feeling.

The parts where Polly tells you how to install R Studio and Git should just be left as scripts/written instructions. Far too pedantic.

Great for getting a solid understanding of where the specialization is heading.

автор: Jonathan K

8 июня 2016 г.

A good but brief introduction to a number of useful skills. I learned a lot in a short amount of time but I still have a long way to go. I was somewhat disappointed in the lack of communication with a TA or instructor. The message boards were desolate and could not support any kind of a robust discussion of the conceptual issues involved with data science.

автор: Débora d C S

6 мар. 2016 г.

The instructors are great, but I think the content of this course should be embbeded in other module. Despiting being important, the topics covered here are very introductory. I recognizes, though, they are important to align expectation and to put everyone in a minimum ground of knowledge. However, I am not sure if Coursera should charge US$ 29,00 for it.

автор: Margaret

4 окт. 2016 г.

It's a good course, but it might be a little too introductory for someone who already has some familiarity with programming (although I hadn't used R, I had other experience with a similar language). So for me, I completed this course much more quickly than I anticipated and was really just very eager to move on to the other courses in the specialization.

автор: Sam E

27 мар. 2018 г.

This should give you a feel of data analytics and help you decide if you should proceed with the entire suite of classes. The course itself is not enough. It needs supporting materials and more practice sessions depending on your experience level with computer science. I enjoyed it and recommend it for people with no background in computer science.

автор: SRINJOY R

7 мая 2020 г.

The lectures are meticulously built for learning perspective. But it would be have been more great if it can be delivered by some faculty in this field. Then i could have understood better. Moreover some real time problem should be given to us so that we can analyze the data and get an experience of how this this course is helping us practically.

автор: Stuart B

2 июня 2020 г.

A limited introduction to R Studio, Github and R Markdown. The "do it all on your own" model of this class worked better than I expected it to. I only had a few points where I thought "There's a defect in this quiz" or "those instructions aren't quite right". How to maintain the quality as it is steadily updated is probably quite a challenge.

автор: J A

19 авг. 2016 г.

This course was a great intro to these concepts and helpful guide to getting things set up and getting used to the MOOC format, as well! A few times it seemed like the slides jumped right in while skipping over a bit of context, but was able to orient myself with some googling and asking friends some basic questions to figure things out.

автор: Jackson B

9 апр. 2020 г.

Overall, wonderful course - but I would request that you change the signature name on the certificate from "John Doe" to a real professor's name. Having John Doe on the certificate makes it feel inane - I would never show this to somebody with whom I was applying for a job, for example. Other than that, loved the course. No issues.

автор: Jim L

5 окт. 2021 г.

I have decades of experience in the field, and am using this to broaden from SAS to R. Much of this was a review (as I knew some R already), but overall I was pleased with the course. Some of the quiz questions were more trivia than what I would call actual knowledge, but those items were inconsequential. A decent introduction.

автор: MOHAMAD A

29 сент. 2020 г.

Great course. The only gripe I have with it, is that sometimes the same question is asked during the tests after each module. Also, I got a lower grade because only 2 people graded my work and 1 made an error. I did get half of the points as they averaged, but still. This however is with Coursera I imagine. Definitely recommended!

автор: Robert S

10 июня 2019 г.

If i could redo this course, I would have taken it simultaneously with the introduction to R course. On it's own it feels like a grab bag of information and it felt like I was delaying getting into the meat of things. That said, the information itself is very important and I found myself referring back to the lecture notes often.

автор: Paulo C M

31 окт. 2016 г.

Good introduction to basics. A few improvements are warranted:

Lessons could be reordered in a more logical progression, particularly when it comes to Git.

Gitbash is not easy or intuitive. A more structured approach (e.g. with cheat sheets, command glossaries, structure diagrams, debugging algorithms etc) would help assimilate it.

автор: Luiz F

22 мая 2016 г.

The course is excelent for people who don't know anything about R, Rstudio, RmarkDown, Git, GiHub and other tools. However, for people who already know a little bit of those technologies, they will find it a little repetitive. Anyhow, the classes are awesome for you to get to learn to use those tools. Congratulations to the team.

автор: UJWAL S S

29 мая 2020 г.

Automated lecture are made using difficult english to understand, it feels like that robot keeps speaking continously without a stop and also the presentations in the videos makes me feel sleepy, if you use facecam that would be better for the learners but not for you i understand that. This course is little far from perfection.

автор: Sandra V

21 сент. 2020 г.

The content was clear and easy the first three weeks. But it was confused to me at 4h week and for the final presentation it was a lack of clear instructions, I was so sad because I had many troubles at the moment of commit, push and fork a file, I had to find external help and I thought I couldn't finish succesful the course

автор: JAVIER D L R A

21 мая 2020 г.

Excellent Course, very simple to understand and concisius. If you wish to learn data science and you dont have any idea about it this this is your course. Only the part of Git I wouldl like to be more explicit, because in one part there is not very clear how we have to create a text file with extension .md using Github. Thanks

автор: Ross B

10 февр. 2020 г.

Course was pretty good but the later lecture videos go really fast and are hard to keep up with. The main problem I had was when it covered R markdown it made no mention of having a LaTex program to create the pdf, I had to spend some time figuring out how to install and get one working in order to knit the markdown file.