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

4.6
звезд
Оценки: 32,682
Рецензии: 6,973

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

SF
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.

LR
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.

Фильтр по:

6151–6175 из 6,863 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Jake P

20 апр. 2019 г.

The lectures are sometimes needlessly long with a lot of superfluous talking. The course would be better with more concrete examples and THE OUTPUT OF EACH INCLUDED. The course explains very simple queries and then asks you to do complex ones in the quizzes when the examples were poorly explained. Khan academy is a much superior course to this one, yet it does not offer a course certification. If this course actually wants to teach people efficiently it should emulate the real-time learning and coding in browser that Khan Academy has.

автор: Dilyan D

9 окт. 2016 г.

This course sets the stage for the rest of the Data Science specialisation.

You get a lot of textbooks for free and they cover a lot of material.

The quizzes are a little bit underwhelming, especially the first week. Too few questions, testing some questionable knowledge (eg, what other courses there are in the specialisation -- hardly a required tool in the data scientist's box).

Overall, it's a good preparation for what is to come. It managed to whet my appetite for more , however I'm not sure the course is very useful on its own.

автор: Amador M d S N

14 апр. 2021 г.

This course talks about the basic of Data Science theory and makes you install R, RStudio and create a Github repository.

The theory part is really nice and well presented. However, the "practical" part is boring (tutorial of downloading installer and clicking in "Next", and the tests ask about RStudio interface details, such as "Which of the options below is NOT a way of creating a new project in RStudio?". And we install R and RStudio, but we don't use them. We see a bit of R Markdown, but nothing of programming.

автор: Chengming X

14 авг. 2019 г.

I have to say the text to voice translation of the text to video lacks good rythm, sometimes it is not easy to follow all the detial espatially there never is natural pause after some touch ideas or steps to me. As a class of introdution level to layman like me I think it could be better introducing more practical examples to practice, or I would like to see some links to external study materilal, that would make the class experience even better to avoiding frequently searching for troubleshooting.

автор: Sanket B

15 июня 2019 г.

The initial lectures were good . The Git & Github part got me little confusing , a little detailed explanation with live examples would have really helped. The last conceptual part was interesting. Some reading material just to drill down on certain Data science jar-guns would really help though it is understood that best place to find answer to question is google / forums / stack overflow...Still some reading material would really be very helpful to maintain the interest in the course.

автор: Vicki K

21 мар. 2016 г.

Basically if you take this course you are paying money to create an account on a website and download some software (both of which you can do for free). The rest of it is a preview of the other courses in the series. The quiz questions don't correspond to the information on the slides. I successfully passed the course, but I didn't really learn anything. Now I am debating on whether or not to continue to the R programming course after reading through the reviews of that course.

автор: Kiiza P

26 дек. 2020 г.

The videos are not good at all it's better the latter where people discuss about the module. It's very boring to watch and listen to the robotic videos. The script bit of data for reading is quite awesome and I believe if it's possible, it's the one that needs to be edited or you can add both lecture videos and those robotics videos at the same time and learners decide which to watch. Anyway the content was relevant and challenging at some point which makes learning awesome.

Thanks

автор: Mariana V B

24 сент. 2020 г.

It's good only if you are already familiarized with Rstudio and GitHub. Otherwise you'll be completely lost, and better off looking for youtube tutorials.

Es un buen curso si ya estás familiarizado con Rstudio y Github, de lo contrario vas a necesitar buscar tutoriales mejor explicados e intuitivos en youtube.

En el fondo, avanzan muy rápido y se saltan muchos supuestos.

De todas formas sirve para practicar con calma, en el caso de que se tenga más intuición sobre Rstudio y GitHub.

автор: Andrew H

12 мар. 2017 г.

This is a good, general introduction. A motivated student can run through it very, very quickly. As the first of ten courses, I understand that it is a very general introduction. Still, I think it could be ramped up a bit. Week 2 of the next course - R programming - is kind of a kick in the head if you're not a programmer. I feel like some of the content from R programming could have be included in the toolbox course in order to take advantage of the relatively light load.

автор: John A

28 мар. 2016 г.

This should be at most a 1 week course, that is free. Half the course is installing Rstudio and signing up for github. The other half of the course is simply learning what each course down the pipeline is about. Those lectures could just be tacked onto the description of each course and you would get the same thing out of it.

I think this course would be improved by more instruction on what git is and how to use it and maybe going over some fundamental statistical topics.

автор: Konstantinos L

10 февр. 2021 г.

I've learned many interesting things concerning github, but the concepts taught in videos were kind of inadequate in some cases. I had to google some things in order to understand exactly the concept. Finally, I am not pleased with the peer graded assignment because even though I had it all right (Correct), someone gave me low mark resulting in stuck in the final stage. I had to re-submit THE SAME assigment to mark me again, and finally recieve the certificate.

автор: Ashish C

29 окт. 2020 г.

This is definitely not a beginner friendly course. Only definitions were covered rather than actually showing how they work. Github part was confusing. Markdown part was not explained at all. You need to be good at searching for your query on google if you want to take up this course but that's something you need to do for every course out there. No single course is complete but still, in this R course you need to be really good at doing google search.

автор: Gavi D

2 янв. 2020 г.

The course was exceptionally planned and executed. One big problem that I had with the course were the automated videos; I can't say for others, but I wasn't at all comfortable with an AI voice teaching me the course content. I don't think I can ever get used to that. I would rather take a course that's 10 years old, 80-90% valid but has a human teaching me the course content. Other than that, I enjoyed the course. Thank you!

автор: Molly H

17 мая 2017 г.

This course accomplishes what it says it will, but boy is it boring. If you are not already experienced in data science, it also requires a fair amount of imagination to picture what all these tools are actually used for. I would have preferred to have these tutorials integrated with the more substantial courses in the specialization. That way I could see how these tools fit in to an actual project.

автор: Ilkka N

2 июня 2019 г.

The course dealt with basic software issues on getting you ready for Data Science, and discussed briefly more conceptual topics. The contents of this course by no means would take 4 weeks to complete from anyone, so I think the time span to take this course is exaggarated. Still, it is very important course to get you started, if you are complete stranger to R, RStudio, GitHub and R Markdown.

автор: Anthony W

5 февр. 2021 г.

It has a lot of potential but it would really benefit from slowing down and explaining steps a little more slowly such as integrating R Studio and Git, and how to use Git and push from R studio to Git. For an online course, there's no need to rush through this content and judging from the comments in the forums, many people have problems with their instructions, or lack of.

автор: Allen D

26 апр. 2017 г.

There is a pretty big jump from the content to actually completing the assignment. The assignments are not well aligned with the swirl learning or the videos. There is no logical process taught about how to move forward if you get stuck. It often means a student is forced to search the internet and hope the answer they find is appropriate so they can write their own code.

автор: Varun B

17 мая 2020 г.

I liked the course, but I'm still quite uncertain on many aspects; feel like I have a lot of grey areas. I think adding a small project video, and how the different tools (RStudio, GitHub, GitBash etc.) come together on a project would have been powerful to clarify how this comes together during a project. Not for us to learn or emulate, but to understand the big picture.

автор: Marco M

1 июля 2020 г.

Establishes an overview of what Data Science is and introduces some necessary vocabulary. The installation instructions and github setup will bore IT-professionals to death, but my be useful to other students. The final test should really be scored by a bot instead of other students of this course -- as it is, it needlessly wasted my time with clickwork.

автор: Sumit S

5 мая 2020 г.

I think first course is only about installing, installing and installing. If they cover more introduction to the field rather than only installing that would be nice. But to show how to install and perfectly run the software is very necessary and the did that job very nicely.

looking forward for the next one hopefully that'll be also good as this. :)

автор: Anushree V P

25 окт. 2018 г.

The course structure is really good. The content is good too. I found the speed a little too fast. Plus there should have been some small exercises in between before the quiz to make the lesson more interesting and intriguing. Another point that I would like to state is that, the slides could be even better and visually appealing than they are now.

автор: Kathryn A C

3 мая 2020 г.

The content is fine, as an introductory course, however, the computer generated lectures are a travesty. There are enough mistakes in the text-to-speech translation that make for a distracting experience, and if you are really a novice, could be problematic. I wish that the teaching staff would go back to filmed lectures with a real professor.

автор: Aketzali A A C

26 мая 2020 г.

Es un buen curso al principio, un poco básico. Te enseña a instalar el programa R y GitHub, siento que si no estás familiarizado con programar, puede que no te sirva mucho. Por el otro lado, si ya lo sabes hacer, puede ser que sea repetitivo.

Acabe el curso en 3 días, así que es un poco breve para el tiempo para el que está programado.

автор: Jairaj A P

26 авг. 2019 г.

i felt this course was very disorganized. It introduces terms and concepts not explained before. There was an assignment on creating forks. This process was not in any lecture. Of course, with R and GitHub you can find anything on internet.

The lectures narrated by Amazon Polly is very boring. It also messes up some of the terms.

автор: Lou O

21 июня 2016 г.

It's ok. After the first lesson, I should be able to provide a clear elevator pitch with a high level understanding of what I can expect to accomplish (4 or 5 steps) as a Data Scientist. Instead, there was one slide that touched on this quickly, somewhere in the middle. What are the problems, how do I solve them, give samples.