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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: 32,304
Рецензии: 6,902

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:

26–50 из 6,786 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Annina H

14 авг. 2019 г.

The course contents are thorough and clear, but the UI and the platform of the web course could use some thought. I find it a bit tricky to take notes and copy url's and command lines from the video. Perhaps this is just a matter of getting use to the platform. Excited to proceed to the next course!

автор: Yujian B

10 июня 2020 г.

Automated videos are difficult to focus.

автор: SHENGNAN Y

13 нояб. 2017 г.

I missed the entire course deadline just because I stuck in one of week 4 projects - pushing a file into GitHub. When I went to the forum, there are so many people in the same situation. The main reason is that the week 4 video did not cover the project content well. Overall, compared to other programming courses I took on Coursera, this course is not well organized at all! Instructors basically just read words in slides, no interesting examples and no hands-on practices, especially week 4 slides that look like a syntax reference document. So the entire instruction is very boring, making me wonder why I need to sit here and listen to word reading rather than buying a textbook. Also, people coming here to learn it are new learners. When the instruction skipped much and made the content not logical and complete, it is very difficult for us to understand what the video is talking about. That's why in forum there are so many people expressing their confusions. This entire specialization is the one that I've taken and feel the worst (I got lost in the R course too). I strongly recommend the instructors of this course watch and learn how the instructor of the specialization "Python for Everyone" organizes and teaches the content. He makes programming become very interesting and easy to understand. He also provides many hand-on practices to help learners understand abstract concepts. Unfortunately this specialization instruction is just about reading words in the boring slides.....

автор: Maria S

27 янв. 2021 г.

I did not like this course for many reasons, the primary one being the automated videos. By switching to this type of video, the course misses the mark on the whole point of taking courses versus reading a book -- one of the big parts of learning is the interaction/relationship you form with the instructor and their experiences and expertise. These types of videos feel very cold and detached and are psychologically not effective or engaging. Additionally, there are many mistakes in the section quizzes, and it didn't really feel like the things taught in this course were worthy of an entire course -- they resembled more of a brief intro to the subject and a bunch of reference appendices.

автор: Tara N

24 июля 2020 г.

Very basic stuff and very dull, monotone computer-synthesized voice. The quizzes are also so easy you may as well not take them.

автор: Senthil K M

11 нояб. 2016 г.

Impressive explanation on the subject., Freshers with no knowledge about the domain can easily understand the subject. Thank you so much for such a fantastic MOOC mode of learning possibility. Love it all.

автор: Deleted A

12 нояб. 2017 г.

Really impressed with the completeness of the learning environment. I would rate this more highly than a traditional classroom because of the interaction and opportunity to go over concepts repeadedly.

автор: Zahscha G

25 мая 2020 г.

I enjoyed the format of this course. It was a good quick introduction to some Data Science concepts, R, and Git. I liked that the same material was available in video/audio as well as reading material.

автор: Clifton H

16 окт. 2018 г.

Straightforward and the tasks aligned well with the instruction. Examples were used to good effect. Highly recommend using the course forums if you're stuck on a problem (especially the final project).

автор: Darky C

27 нояб. 2018 г.

Pretty good in explaining the basics of data science

автор: Adeyemi O A

10 янв. 2019 г.

Very good course for beginner in data science

автор: JEFFERSON D S N

31 авг. 2018 г.

SIMPLESMENTE SENSACIONAL !

автор: Allyson D d L

7 сент. 2021 г.

Just an introduction. I learned about Git and how to integrate RStudio with Github. It was interesting to me. The activities were so confusing and ambiguous and all the course is with a robotic voice. It makes the course a little bit weird. But in general it was good and fast to conclude. The total duration of the course could be halved because all classes are given twice: in video and in text. But you can not download the slides or any PDF lecture.

автор: Maximiliano F M

12 авг. 2020 г.

Its a basic course to learn general terms of data science. It helps you to set up all the programs that you need to start in this discipline: RStudio, Github and some additional good practices. In general, its a good course. However, I missed coding and a person explaining the videos (i understand the idea behind this, but the concepts on this particular Mooc are so introductory that the argument is not valid for me)

автор: Usenaliev N

8 дек. 2018 г.

Would be great to have more reading materials

автор: Aman U

5 янв. 2019 г.

Good but need more explanations for topics.

автор: PALAKOLLU S M

10 авг. 2018 г.

Teaching of lessons are simply amazing.

автор: Jasmine P G

16 авг. 2018 г.

The course is clear and good to learn,

автор: Md. Z M

23 мая 2020 г.

The course is well structured with enough content provided on each topic. However, the steps to install softwares on Linux, or any instructions to complete the setup on a Linux machine, is missing. Also, I feel that the course is so basic, both in content and duration, that it could be accommodated easily in a few lectures in the next course in the Specialisation. In a nutshell, it doesn't deserve a price tag.

автор: Lakmini R

8 июня 2020 г.

It was basic but was very helpful. However, more things on actual data science should have been included in the course

автор: S. R

11 июня 2020 г.

Computer voice is not good to listen otherwise the course will be a great material to start data science.

автор: S.M.Abid R

20 июля 2020 г.

It seems very basic

автор: ANURAG A

10 июня 2020 г.

Robot voice should be replaced by the course instructor's face to face interaction.

автор: Robert T

9 июня 2020 г.

Good course content but I really disliked the robotic voice used in the lecture.

автор: Adam C

21 июля 2020 г.

I started the course but didn't like the computer based audio lectures.