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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

Оценки: 32,694
Рецензии: 6,976

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

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.

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:

4901–4925 из 6,865 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

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.

автор: ramanathan l

7 апр. 2016 г.

This is a fantastic course, being a person who already works with loads of data I can surely stand by the statement that "This is a fantastic base line to all your data needs"

автор: Vishal M

22 мая 2018 г.

Could provide live demo of creating markdown file & pushing into the remote repository.

Overall the learning was awesome. Was a good guide to go forward to subsequent courses.

автор: Greg S

15 нояб. 2017 г.

Straightforward (although I am already familiar with markdown and git, so that helps). Lots of good groundwork here though, setting the scene for the next round of material

автор: Shaik M U

20 февр. 2017 г.

Coursera has changed the way of learning,Yes anyone can learn anything and everything at the comfort of their own time and place......

Thanks Team COURSERA....Keep Going....

автор: Brandon B

22 мая 2016 г.

It's a good introduction to data science. However, without prior knowledge of statistics, programming, and research methods the course would be fairly difficult to follow.

автор: sharraf t

2 авг. 2020 г.

the robotic voice got a bit annoying towards the end of the course, but overall i like the course and found it informative, cant wait to continue with the specialization .

автор: Willie C

21 янв. 2020 г.

This course is fairly rudimentary, but it does a really nice job of getting you all set up with the tools you'll need to tackle the rest of the Data Science specialization

автор: Hannah B

4 июня 2019 г.

The part where GitHub, Git and R are connected was very interesting. However, as a fairly experienced R user and scientist, I wish I could have skipped some of the parts.

автор: Ashley B

31 мар. 2021 г.

The robotic videos are crazy different from seeing an actual person on a video like in the IT Specialization. That's my only real complaint, otherwise, I learned a lot.

автор: Luis E R R

29 апр. 2020 г.

I found this course to be quite useful, albeit introductory. I kind of was hoping for more material. Nevertheless, for a beginner, I believe it is completely appropiate.

автор: Neha S

10 окт. 2016 г.

Good start for the beginners especially for people new to the data science. Topic are not covered in depth but as its just a introductory course so its totally fine..

автор: Mechell S

12 дек. 2020 г.

A great introduction to the world of data science. This course gives a good foundation of what is expected as a data scientist and the tools required to complete task!

автор: Alex B

26 авг. 2019 г.

Well explained, step by step instructions on how to install and use the tools

Potential to improve: use more visuals in de instructions (many times now it is only text)

автор: Mark M

1 июля 2018 г.

Provides a good overview of what will be learned in the Data Science specialization. Good introduction to the software tools required and how to set them up correctly.