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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

4.6
звезд
Оценки: 32,331
Рецензии: 6,904

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.

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101–125 из 6,789 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Jay D

27 июля 2018 г.

It was a great start of the specialization course. I completed in just one day. So in fact if you get a time of 4-5 hours in any holiday or free day just do this. It will create interest in you to learn more and more with quick space. I highly recommend this course to the people who has some interest in data science and want to learn more but doesn't get a clue where to start. This is actually a perfect platform to start .

автор: Catherine I

28 июня 2019 г.

Very good course to get the basics of what the overall specialisation will entail. Great information on setting up your system for any of the other courses in the specialisation. Information on Command Line programming and version control with Git and GitHub set-up proving to be useful. Good to get an introduction to the process of submitting peer reviewed assignments for future courses. Overall good introductory course.

автор: 黄雅妮

15 окт. 2019 г.

This course is perfectly suitable for people who have passion in R or data science, and has some basic concept of statistics but not a specialist yet. I am a undergraduate student majoring in public health .I choose R for my first scientific tool because of its various utility and applicability to data analysis. But I also want to try to learn some Python in the future. Thank you professors, and my dreamy school--JHU!!

автор: Dhiraj K

5 нояб. 2016 г.

To start with, I have enjoyed this experience of online learning a lot and this is my first online course. The structure of the course is very well designed. The platform is very user-friendly. Although it was just a basic introductory course, it is just a step towards learning more interesting things from a renowned university and very good professors. Looking forward for more quality courses. One step at a time!

автор: Jade K

23 июня 2020 г.

Comprehensive set up guide and good staging for how to truly be effective in using data to answer questions. Only feedback would be that links should be made clickable from video page and perhaps that notes should be made downloadable. I'd also suggest that when a question is answered incorrectly, recommending users reread notes instead of rewatching the videos as it's easier to skim notes than it is a video.

автор: Angel R G J

12 июля 2020 г.

I enjoyed the lessons. I appreciated the lessons being available in both video and text. While watching the videos I would follow along with the text and if the topics were very technical or heavy with new information I would read the text lesson a second time to help the information sink in. Additionally having the support from the lessons and forums while building my data science toolbox was very helpful.

автор: Gabriel V d O

9 мая 2020 г.

The teaching methodology of presentation were excellent, I was a little disappointed for not having any more applied exercises. But I believe that my expectations were high and it was necessary to focus only on the tools on this stage. I imagine that this must be the content of the next modules, which I am looking forward to doing. I thank Coursera and JHU for the opportunity granted by the scholarship.

автор: Lourdes S

26 дек. 2019 г.

It is a great course for begginers in Data Science. The videos are clear and easy to understand for non-english native people. I think it is overwhelming the first step with the tools: R, RStudio, Git and Git Hub, but, if you dedicate enough time to read the material and manuals, you can do it. The fourth unit was delightful. I learn a lot and I want to say thank Coursera and JHU for this opportunity.

автор: Ron L

10 авг. 2018 г.

I have had a Github account for about a year now and I have never used it. Version control is an important part of programming and data science process so being forced to use it by via assignments was a great touch. I am comfortable loading repos now and I have the tools to use Git to have it on my local machine. A great introduction to what is turning out to be a pretty exciting and beneficial class!

автор: Yi-Wen C

25 сент. 2019 г.

It is a great intro for a beginner if you want to get to know Data science in a broader way. I highly recommend people who are interested in data to join the course. Besides, the course doesn't have to spend many time every week. The content of the course is organized well in a slow path and can also gain more confidence after taking the course, which may be helpful for the following learning.

автор: Clare G

17 февр. 2017 г.

Very well received by this beginner. I appreciated the time taken to offer an introduction to the command line, which was focussed on the immediate commands needed to continue with this course. Many other data science courses either overlook any kind of command line tuition, or they point you to an overwhelmingly large other tutorial on the subject which would take you 3 weeks to complete.

автор: Charles D

5 июля 2016 г.

This is a nice course on getting and installing the data scientist's tool box. In the future, this course should be improved with an example of creating files in Git and pushing them to GitHub. Although issues were addressed by peers in the class, going through an example before the course project will very much help future students with no experience. Great course. I highly recommend it!

автор: Christopher A C

28 мар. 2016 г.

This is a wonderful introductory course. I allows one to get an idea if they would like to continue towards the specialization. I would suggest taking this course with the R-Programming course. I have a very basic knowledge of Data Analytics and I could have taken the first two course simultaneously. However if you have a incredibly busy schedule just taking this course would be fine.

автор: Brooks A

1 окт. 2020 г.

This is a great course to help you set up the tools required to start a data science project. The pacing is perfect. Each lesson conveys just the right amount of information without being overly explanatory. I had some issues receiving feedback on my end-of-course project. However, this is not the fault of the instructors or course content. Rather, it is a flaw in the Coursera model.

автор: Francis P

29 окт. 2019 г.

I recommend that beginners, coders new to data analysis and anyone seeking foundational experience with Git, collaborative coding or the R programming language start here. It does not dive deep, but does introduce interfaces, basic syntax, routine operations and some commands in the technical setup portion, and also goes into test design and glosses the general field of study nicely.

автор: Justin A

15 июля 2019 г.

Excelente curso. Brinda una introducción a la ciencia de datos (Data Science) y las capacidades de este campo. Se configura RStudio y se aprende a utilizarlo, junto con los repositorios de GitHub, y se muestra la manera correcta de obtener ayuda con los problemas que puedan presentarse. Al final, se crean archivos con RMarkdown, y se introduce Big Data y el pensamiento estadístico.

автор: Sheri M W

7 июня 2016 г.

This class is a great introduction to the tools needed to begin working on data analysis. The assignments provide just enough instruction to cover the basics and propel you toward uncovering additional information on your own. The assignments are structured in such a way that you must pay close attention to the lectures; then analyze and apply them on your own. Great course overall.

автор: Rachael M

25 июля 2020 г.

Learned SO MUCH! I can't believe how much I actually learned. The course is set up so you are forced to download and practice using RStudio and Githun (both free), and are guided through it. Not too hard, not too easy either. Just challenging enough. Also appreciate that I didn't have to spend 10k on a bootcamp when I wasn't even sure that I liked data analysis. Now I know I do!

автор: Arijit D

27 дек. 2017 г.

Beautifully set series of lectures that gave an in depth view of what Data Scientists are thinking of in this modern era of human excellence. The slide font to be slightly increased and the sound quality too.

My teacher of the course has given his best and their could be no comparison of his efforts.

Thanks to team Coursera for setting up such a beautiful set of learning material.

автор: José A R N

16 окт. 2017 г.

My name is Jose Antonio. I am looking for a new Data Scientist career ( https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.

The course was excellent and the classes well taught by the teacher.

Congratulations to Coursera team and Instructors.

Regards.

Jose Antonio.

автор: Sai C

9 апр. 2020 г.

It was a great Toolbox..!

It seemed to be simple but yet it was challenging as it was the first time I was exposed to Data Science, R, R studio and even GitHub.

It effortlessly made me focus on simple tasks.

Which made me more curious about how effective other courses might be.

Looking forward to learning and growing my skills with this wonderful platform.

Thank you, Coursera...!

автор: Nino P

24 мая 2019 г.

Not really interesting course, but good for start. You won't learn much beyond setting up github account and downloading R, but it fits well in the overall specialization. The feel is that this course is like the first day of school, you don't do much of work, but you still need to come. I do not recommend taking this course alone, but I do recommend taking the specialization.

автор: Mohammad K A

17 сент. 2018 г.

The Data Scientist’s Toolbox Training helped me learn the elementary and essentials of data science concepts as well as it is interesting project submission and reviewing others’ submitted projects. It is an incredible learning experience from Coursera’s Data Science Course from Johns Hopkins University industry experts. I would like to rate my Data Science instructors a 5/5.

автор: kalluri v r

13 февр. 2016 г.

The Data Scientist's Toolbox the second course that i have taken in the Coursera. I have completed this course in a short time but the course is awesome and providing info from basic and videos are helping a lot. I think to become a data scientist this is the best place to start pleased to complete rest of the course also. Thank you Coursera for providing such awesome course.

автор: Jose R

19 дек. 2020 г.

Awesome! To know how to deal with technical difficulties and get familiar with R and R Studio before even programming it's a good first step and certifies that i will be a reliable Data Scientist because i will be able to deal with installation issues and compatibility situations without depending on others for thriving in my own work. Highly professional, thanks very much.