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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: 22,598
Рецензии: 4,565

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

LR

Sep 08, 2017

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.

AM

Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

Фильтр по:

126–150 из 4,438 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Arthur D

Apr 11, 2016

Very good introduction to data science. It gives a general overview on data and its problematics but also tips and help on how to start with the basic tools that will be needed (I haven't done any R programming and didn't have a github account so that was helpful for me).

автор: Anatoli K

Mar 14, 2019

Интересно было посмотреть как работает один из лучших исследовательских университетов мира.

Кроме настройки программного обеспечения много узнал об основных принципах науки о данных.

Очень понравился пример с Хилари Клинтон. Возможно это был роковой момент в её поражении.

автор: BHAGAWAT M

Jan 29, 2020

It's really enjoyable, a lot to know and a lot to discuss. The other links provided for more details are very much helpful. The feature of the discussion form is very helpful. Thanks, to Coursera and the team of Coursera for your high great work to open this platform.

автор: Juan C J T

Jun 12, 2018

Muy buen curso introductorio en el que se pueden observar las herramientas necesarias para realizar análisis de datos, además de que muestran quienes son Científicos de Datos en la actualidad y qué tipo de análisis realizan, todo adquiriendo la información de internet.

автор: Daisuke I

Mar 07, 2016

Setting up the environment is often the tricky part that deters people from moving into, or back into coding. This class provided me with a hand-holding needed to start coding again. I recommend this course as a kick starter for those who were on legacy environments.

автор: Ahmed M K

Oct 01, 2016

What a great introduction. It needs a lot of reading and self developing to be able to do that project at the end. It's kind of difficult but you'll feel that you've really learned something that will be useful for the rest of your life. Thanks JH and Coursera staff.

автор: Joan S D C H

Sep 06, 2019

Es un buen curso. te lleva de la mano pero no te da todo digerido en cierto momento debes buscar alguna solución para las tareas que te piden pues por razones de versiones ya no funciona igual.

Sin embargo el contenido temático es lo importante y me pareció perfecto.

автор: Richard E H

Apr 27, 2018

A good introduction to analytical processes and tools. The course by itself, however, is only a first step. I find many threads begun but not tied together. I anticipate that the remaining nine courses will expand and consolidate everything opened in this course.

автор: Kevin C B C

Nov 06, 2017

A very eyeopening introduction to the discipline of Data Science. Hope this prepares me for R programming soon. :) I also realized how relevant this is today especially in the sciences, wherein one must have a good grasp in programming as an aid for research.

автор: Roberto A

Mar 11, 2017

I found this intro course really useful as a warm up and to get into the "data scientist's mindset". The only (minor) point for development is to devote more time to Git and Github, as some of the steps were not particularly straightforward. Well done though!

автор: Eduardo d S A

Feb 07, 2017

I really loved the course. My peers were amazing. They always help and when they review your project they make sure that you will understand what you did wrong, explaining why and how you might gei it right the next time. Mr. Peng you are amazing. Thank you!

автор: Sandra N

Aug 22, 2016

This is a fantastic way for individuals to get a leg up if they want a competitive edge in an ever-changing scientific environment. It is important to be able to use certain programs and code to some degree in order to be competitive using today's technology.

автор: Drew W

Aug 24, 2019

The course was well put together and documented. My only critic is that I would like the lecturer to go over Git and Github more thoroughly as I had to do some extensive outsourcing to be able to figure out how everything worked. Overall, a very good course.

автор: Saurabh C

Jun 09, 2016

Best in it's Class. Short but so much descriptive with a constant effort to deliver high quality teaching with easy understanding language and concepts!

It's highly recommended to those who are new to Data Science, and want to make their Base strong( like me)

автор: Rabindra T

Nov 27, 2018

Really nice intro to the set of tools to be used. Step-by-step instructions. It might be useful to have it called out that versions may change, but the basic video instructions will not. There were slight updates that made things look a little different.

автор: Joe D

Feb 20, 2019

An excellent introduction to r, rstudio, and the basic concepts and functions of github (online version control for personal or collaborative programming projects). Great course, informative videos, lots to do and experiment with, I highly recommend it!

автор: Rahul G

Jun 24, 2016

Extremely helpful. It was detailed and at the same time brief, made sure I am able to connect with the content and learn in ways that will be useful in career.

Also, the exams and exercises made sure that my concepts are deep rooted into me.

Great Course.

автор: Ahmed M

Feb 11, 2016

Pretty easy and straight froward, for someone who is already familiar with Programming Editors, and Git shouldn't take 2 hours for him to finish this course including its project, so I guess it's an exciting start for someone who is new for Programming.

автор: John A R B

Aug 13, 2016

In this course was proposed the outline of the specialisation, showing in a practical and interesting way some of the principal points in the path to be a Data Scientist, I was wondering by the exposition and decide to finish the whole specialisation.

автор: Jessica M

Nov 05, 2018

This was a very informative course and a good start to the Specialization. The course project I found to be very challenging, only because I am not familiar at all with Git and it took me a long while to figure out the right commands to perform tasks.

автор: Felicia S

Apr 06, 2020

Some people might say that it has lots of theory, but I find that the theory is delivered in a way as succinct and impactful as possible within the short video time. Do read the written material to understand the intricacies of the in-material jokes!

автор: Dev P

Oct 25, 2019

Great introduction into the world of R! I have been completing this alongside the R Programming course and found the two go well together. Interesting to learn about version control and utilising Github, which I am sure will be valuable in the future

автор: Meihan L

May 16, 2018

4.5/5. For a total beginner of data science, sometimes the lecture is hard to follow so I have to resort to several youtubes videos to complete the project. But the lecture is informative and well-structures, and the forum is very helpful. Thank you!

автор: Juliana C

Oct 06, 2017

This first course of the specialization is extremely important for people like me who do not know nothing about programming, coding, computer data, etc.

When I completed the course, I was more confident to continue with my idea to start a new career.

автор: Yash S

Jun 03, 2018

Really intimidating, but very attractive introduction of what lies ahead by portraying a true picture of what you would be involved with as a data scientist in future. Looking forward to the courses ahead in the specialisation. Thanks you so much!!