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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: 29,965
Рецензии: 6,391

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:

151–175 из 6,248 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Shannay R

3 мар. 2020 г.

An excellent introduction to R, RStudio, Git and GitHub. The course content is well designed and touches upon various topics in a crisp tone. The course lowers inhibitions and allows learners without any coding experience to test the waters.

Definitely recommended for all enthusiasts looking to venture in Data Science

автор: Jose P M L

9 июля 2020 г.

Very nice introduction to the subject. If you know RStudio and Git you can easily go throught it in a couple of days. You might really wanna go deep into R Studio features like markdown syntax and take a good look at Hilary Parker's work to see how a data scientist think and go through her process. Her blog is amazing

автор: 20e

12 окт. 2017 г.

I got a general idea about the work of a datascientist which laid a stepping stone for my further study.

Further more, I think the lesson of "getting help" is quite helpful and practical for me and I enjoyed the whole class.

I would recommend any one who is interested in datascience to take this course at the beginning.

автор: Ващенков В В

21 февр. 2019 г.

Info is compressed but it is still available for understanding and useful. But I think new students can have some difficulties with git or github, because theres some not so obvious commands like swap branch, commit changes etc...But it is also good for students to learn use Google and look forward for tutorials :)

автор: Francy G B

12 июня 2020 г.

Este curso me permitió explorar algunas de las múltiples herramientas que tiene R y conocer su utilidad en la utilización y/o procesamiento de datos. Además el interés por seguir aprendiendo más sobre el manejo de R, puesto que es una excelente opción, para apoyar el análisis de datos en procesos de investigación.

автор: Marko N

1 дек. 2015 г.

The new graphic is really nice and helpful. Even the fact that you can retake the quizzes after 8 hours is really nice. I have noticed that there wasn't any possibility to download pdf files of the lessons (or I didn't see it), the last time I took the course there was this possibility and I found it so helpful.

автор: Tejaswini P

30 мая 2020 г.

I found this course very interesting. The progression of course from week 1 to week 4 was very well paced. The study material provided in form of notes, powerpoint presentations and videos was adequate for understanding the topics. I would definitely recommend this course for people interested in Data Science.

автор: Jekabs B P

12 мар. 2020 г.

Well designed course; great for first in sequence. On a couple of parts I had to struggle to figure out how to complete an installation or proper launch of a program, but between the instructor's instruction, classmate's comments, and google searching, all was completed. Thank you for designing a great course!

автор: Ravi K M

27 мая 2018 г.

This course serves as a introduction for all the remaining 9 courses to come. You will be learning GitHub, R studio and a bit of command line to be familiar with the tools needed for Data Science. I highly recommend this course for anyone interested in Data Science. The professors teach the concepts very well.

автор: Nedino L C

18 апр. 2019 г.

I really like your approach on making people who are new in this field understand most of the basic concepts. I've been in software industry for so many years now and the reason why I took this course is because I am planning to include most of your courses on my team enabling program. Many thanks and cheers!

автор: Ahmad A

14 апр. 2020 г.

The course was really easy to navigate through. I like the idea of automated videos since it allows the content to be up to date, but it seems that this was not the case (from the given examples).

Basic principles were also explained relating to data science, big data, types of analyses, and other concepts.

автор: D. C R

8 мар. 2020 г.

The content of course was in depth and ease of understanding step by step. The question at the end of each session was refresher for the learning had in that particular unit. Over all it was an awesome experience and passionate to keep learning new things. All the best Team Coursera for a smooth experience!

автор: Aaron B

23 окт. 2019 г.

The main purpose of this course is to get R and RStudio installed on your system, set up a GitHub account, and connect your RStudio program to your Git account. Some time is also spent introducing basic concepts about Data Science. This course is simple in scope, but very valuable and effectively delivered.

автор: Kunal P

25 окт. 2019 г.

Learning experience is much better. I like how they don't give you all the answers in lecture which forces you to research/figure things out through lots and lots of practice. Thank you for all these courses and without hard work by these professors/staff this experience wouldn't have been possible online.

автор: Ulrike H

25 мар. 2018 г.

The course provides a nice overview over the basic tools of a data scientist. The presented methods of the course are up to date. The course materials are concise. Jeff explains clearly and structured. I like the course and, although I've been working with data science for a while, there was something new.

автор: Ana M

30 июля 2020 г.

This was a great first course. I appreciate the video and having the written version together because I can go over immediately something that I might have missed or not understood well. The entire format of the course is great for learning on-line. And the material is well written and easy to understand.

автор: Ashja A K

9 авг. 2020 г.

It was amazing to learn the things from john hopkins , good experience learn alot i will try to practice more and more so that i will never forget what i have learnt this is the starting of my skills i am pretty sure that they will allow me learn each and everything i want to learn reagarding datascience

автор: Dianne H J

17 янв. 2018 г.

Course had a LOT of information. Really appreciated the hands on assignments (although it was kind of scary for me to be installing software in "terminal" mode on my Mac from remote servers). The lectures are done so well, full audio/visual and downloadable slides with supplemental links and documents.

автор: Rahul S

12 мар. 2017 г.

Course is presented in very lucid manner and give you ample information to learn from scratch. Great course those who don't have any background in data science and willing to learn it. Pedagogy is highly appreciated and assignments are never like fun activities that John Hopkins are crafted for learners.

автор: Suki

14 нояб. 2020 г.

Great course for learners who want to step into the world of data science. Lessons covered version control using Git & GitHub and the functions of R and RStudio. Detailed instructions were given on bridging them all together to create the ultimate tool for collaborative data analysis. Loved the course!

автор: Pranith N

27 апр. 2020 г.

The course was very informative and I admired the way they scheduled and organized the course , it was very easy to understand and moving on with it.

at the initial I thought it was rushing through the content but as i started going on there phase of speed of teaching , I managed to get to there speed.

автор: Jerbie D

19 сент. 2019 г.

a really nice introduction for data science :) Although the Text to voice was a bit weird at first, I got used to it very soon. It's one of my first online Courses to complete and I really like the format. You can actually complete the course in less than a week if you have the time. Very worth it!

автор: Oliver G

11 февр. 2019 г.

Ideal for anyone who has never had any experience in the subject of data science. The course lays a nice foundation of what you need to know for the next courses in the specialisation. I would say it is 60% conceptual, 40% technical, which for me is just the right mix to get started on the subject.

автор: Gauranga P S

3 мая 2020 г.

Learning Data Science has always been a passion for me. Thank you Coursera for providing such a beautiful, wonderful platform for education. Faculties are skilled and interact lucidly. Again Thank you John Hopkins University and everyone associated with it in making these course a successful one.

автор: Deleted A

5 сент. 2018 г.

I think this course is really suitable for beginners like me, who have no concept of Git, Github and don't know what data science are doing roughly. Maybe for some experienced learns this is trival, but no one would be annoyed by it since they can quickly pass this context and turn to next course.