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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: 29,916
Рецензии: 6,382

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
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.

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.

Фильтр по:

4401–4425 из 6,241 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Rajanikant T

31 авг. 2017 г.

This is just a basic overview into the world of data science. I would recommend only to the students just starting out in this field. Still, is a good course starting out. Have fun !!

автор: Fouzi T

12 авг. 2017 г.

Thanks to Johns Hopkins University for this helpfull course. It helped me a lot to understand the fondamentals of what data science is and the bueatiful tools used by data scientists.

автор: Ximena V

17 июля 2016 г.

All excellent and a very good introduction. I wish I was able to get my quiz graded without having to pay just to see if I was learning. For the rest, I recommended for a great intro.

автор: Pat S

21 апр. 2018 г.

This course describes the overview and useful tools for doing data science with less details. The material only prepare you for taking the other courses in the specialization track.

автор: Felipe K H

4 апр. 2017 г.

Overall the course is very good and well paced, but I believe it could be a bit more clear in the git and github lessons on how to push from your local repository to your remote one

автор: Stella L X T

30 мая 2020 г.

Not bad to start off with! It teaches installation of all the required things for starting off R (e.g. RStudio, GitHub), and gives a basic understanding of experimental design too.

автор: Javier A P O A

27 янв. 2020 г.

Al inscribirme en la especialización figura el español como uno de los idiomas en los que se dicta, pero no estaba disponible para este curso, por eso lo clasifico con 4 estrellas.

автор: Zili D

16 сент. 2018 г.

Great course. But sometimes it's a little bit difficult to follow, because the instructor just listed those Git commands without actually demonstrating how to use Git step by step.

автор: chad

8 сент. 2018 г.

I was already familiar with the stuff taught for the most part. I think they should do more tutorials on how to install and do things though for those not experiecned enough in it.

автор: James C

12 авг. 2016 г.

Good introductory course pointing to background reading materials and providing context for following courses as well as supporting the installation of the required software tools.

автор: Renzzo S S

31 окт. 2020 г.

Excellent course to start from zero! if you have some knowlegde or a little of selflearning you can only take the weeks that has theory, others are how to install R and its tools.

автор: John E M

9 июля 2018 г.

Seemed simple, but had to figure out some things that weren't explicit in the videos for the exams. Helped in my learning, but frustrating for a very pure beginner in programming.

автор: Pinko W

7 сент. 2017 г.

Professors could extend the videos by more examples and illustration for deeper understandings of the students. The tests could cover more items and deeper contents of the course.

автор: Subhankar J

23 июля 2017 г.

A little more could've been explained about Github, overall the course was highly comprehensive with regular quizzes and assignments helping me to identify my mistakes and on them

автор: Jonathan R

31 янв. 2018 г.

I would like this course to be longer. To have more practices and to have at least one lab with data for running some simple functions. Other than that I think is a good course.

автор: Gavin D

27 апр. 2016 г.

Practical to do if you are continuing with specialization. Ensures all students have the correct setup, which is important. I'm not sure how useful it would be on its own though.

автор: John C Z J

29 февр. 2016 г.

Gives a great foundational overview of what Data Science is, as well as getting your technical environment set up for the future classes in the Data Science Specialization path.

автор: Deepsagar V

26 авг. 2020 г.

A great course content by using machine to teach you. However it is little fast and few things got unclear. Especially Rstudio and Gitbash. Need to study it from other sources.

автор: Parimi R S S

30 авг. 2019 г.

I have expected that this course would have given me the basics needed for my data science specialization I strongly recommend a new optional course which gives all the basics.

автор: Ahmed S

29 дек. 2017 г.

Very good introduction to Data Science and I found it highly useful and insightful.

The main issue I faced is that problem statements are not always clear for programming tasks

автор: Juan M F M

1 июня 2017 г.

El curso me gustó, considero que fue una buena aproximación hacia el mundo de los datos y sus herramientas. Espero seguir aprendiendo en el transcurso de los siguientes cursos.

автор: Ruben D W

9 мар. 2016 г.

Good introductory course, but could offer a bit more of a challenge, with actual (basic) problems. Learned about R, although not programming, and more about GitBash and GitHub.

автор: LI D

29 дек. 2017 г.

It's fairly good! Concise intro to DS. However, you will need to spend more time in CLI and GitHub by looking for information in the forum or googling step by step procedures.

автор: Rachel K

27 дек. 2017 г.

I was able to set all the programs up that I will need to program in R, but I still feel like I don't really know the basic overview of what I will be doing in this specialty.

автор: Philip W

18 окт. 2016 г.

Useful introduction to the world. Could have been a bit longer and gone into more detail about a variety of other factors is my only comment, but overall pretty happy with it.