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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: 29,887
Рецензии: 6,376

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:

251–275 из 6,235 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Melody K S

20 янв. 2018 г.

I am not sure how to assess, I'm advanced in many cases and gaps in others. GIT is making me crazy b/c I can't see it but logic and flow of hub makes perfect sense due to extensive SAS/STATA coding experience and stats background overall pleased.

автор: Daniel S

30 янв. 2017 г.

Great and very informative ! I strongly advice to anyone who wants to start learning how to manage a data and be involve in data science field. This is an absolute course to become familiar with the essential software and technique to get start!

автор: Nirav D

2 апр. 2016 г.

This is the first course in the Data Science Specialization series by Johns Hopkins University taught on Coursera. It introduces all the tools necessary for subsequent courses on data science and gives a driving motivation for the specialization.

автор: Carolina S

8 окт. 2020 г.

This course is the right choice for those who want to get solid foundations of R and version control. I definitely recommend it!

The materials provided are of very good quality and they come in different formats: audio and written, with pictures.

автор: SURJEET K S

17 окт. 2018 г.

This is the first course in my last few online courses of R where I learnt how to initiate Git and Github and do things in a very formal sequential manner. Very good for people who are not too technical in nature. Simple and easy to understand.

автор: Ana D

30 июня 2017 г.

Nice course, very complete, although being new to it I would have loved a longer lecture on thisas well as a practic examn or something similar with the objective of developing this skills sufficiently for future courses fron the specialization.

автор: Syed M A T

28 июня 2018 г.

I have tried to learn a couple of times but due to busy work schedule i always left in the middle of a course or tutorial. However this course due to its interactive nature kept my attention. Finally i completed my first course in Data Science.

автор: Pradeep p

10 нояб. 2016 г.

Course Structure is good. I could able to gain the basic knowledge & ideas about tools & questions Data Analysts work with, then could also get practical understanding about the sharing & version control tools.Looking Forward for other Courses.

автор: Jeff L J D

3 окт. 2020 г.

Thank you very much for this course, this course helps me to have a good understanding on how a data scientist works and what are the different tools needed to work and collaborate with a different professional to work with a specific dataset.

автор: Abbid A

28 июня 2020 г.

Guides students through the basic tools all data scientists need and sets them up to both learn and apply them. A very good introduction that not only covers the theory behind data science but also shows how it can be used in the modern world.

автор: Dostonbek K

3 нояб. 2020 г.

So far, although I am studying computer science, I was too far from the nowadays-popular concepts Big Data, data-analysis (what I am very interested in) and This course covered and gave me the motivation to keep on studying the specialization

автор: RASMI

31 мая 2020 г.

I really loved the quality of the content being provided. I appreciate the fact that the courses have been designed for being beginner friendly, but at the same time it ensures that the student gets to know about all the relevant content too.

автор: Dr. S M A T

12 июня 2020 г.

Excellent Course designed to learn insights relating data science using R software. basic Coding and analytics basics are taught in this course. Moreover learning relating how a data scientist can collaborate on GitHub is an added advantage.

автор: John

22 апр. 2018 г.

This course was a lot of initial set up for the rest of the program. Basically just setting up programs and getting accounts ready for future study. All in all a good start, I expect material and course work will significantly pick up now

автор: Ajay S C

22 авг. 2017 г.

its a nice course to introduce you with the tools required ahead in this journey of data science learning. It helps you in taking that first important step for moving confidently ahead in this great learning. Keep up the good work coursera

автор: Eugene V

30 авг. 2020 г.

Content is not so engaging but I think the new format (text-speech) will help improve the course delivery. Topics are discussed thoroughly and if a certain topic will not be discussed in detail, links to additional materials are provided.

автор: Michael M

28 мая 2020 г.

Exactly what I wanted from an introduction. I feel prepared to begin the more challenging courses in this specialization.

This course isn't so much a value-add on its own, but is designed to set students up for success in a specialization.

автор: Muhamed N A A

17 дек. 2017 г.

Though it was a ground basic skills, but yet solid to build upon. This course helped me a lot getting a clear picture of what is data & data science and the necessary tools required to analyize & generate actionable data.

Thanks Coursera

автор: Hemanshu S

5 дек. 2017 г.

This is really good course and overview about Data science. I had great start for course and Git and basic commands of Linux after several years.

This course will definitely give me exposure to think in best future stream of IT industry

автор: Lam Y H

23 авг. 2017 г.

A great introduction to Data Science and the necessary tools required for the remaining course. Fairly simple, but more catered to a warm up for the remaining courses. Would encourage everyone to continue to complete the specialization.

автор: Hasan B

11 янв. 2020 г.

A very good, organized, and interesting course that teaches you the fundamental introductory elements conserning data science, and helps you learn how to set up essential tools in order to begin learning R programing and using RStudio.

автор: Sean S

26 дек. 2019 г.

I thought this course gave a great introduction to the topics being covered in the Data Science Specialization. I think the only thing I would of liked to of seen is more case studies and maybe some more supplemental reading materials!

автор: Sheikh A

25 мая 2018 г.

Eases into the world of Data science. I do not know if things are as equally easy as this in the future or is this the calm before the storm. Either ways, I'm very glad I took this step, and would recommend this to any one considering.

автор: Frederico P

8 нояб. 2020 г.

Great course, with thorough explanations regarding types of data, data science, the importance of version control and begins to introduce Big Data. It is complete and gives an excellent ground to start developing your first projects.

автор: Serbay S

9 мая 2018 г.

Content is sufficient for really beginners or who do not have previous experience . I learned about Data Science, Git and GitHub usage. I am planning to continue to next courses of John Hopkins University. Thank you for instructors:)