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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: 31,736
Рецензии: 6,752

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:

251–275 из 6,613 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Andrés F N A

8 июня 2020 г.

This course allowed me to understand the relationship between codes, repositories, version control and especially with RStudio to discover the infinite possibilities of using R and the knowledge received in the course of safely undertaking data science

автор: Alexander R

13 авг. 2016 г.

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

5 нояб. 2018 г.

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

6 апр. 2020 г.

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

25 окт. 2019 г.

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

16 мая 2018 г.

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

5 окт. 2017 г.

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

3 июня 2018 г.

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!!

автор: Sreenivasreddy R

28 мая 2018 г.

The course is very structured, simple and to the point. We get a very good introduction to all the tools that are used by the data scientist. This module is like a MAP of all the tools that we are going to learn & master to become a data scientist.

автор: Lakshmi

17 окт. 2016 г.

It was an interactive session. The introduction to the tools and the examples related to various models were relatable. I am glad to have joined this course. The peer graded assignment is a good option to learn different methods in problem solving.

автор: ABHISHEK K S

2 дек. 2018 г.

The course is very good for the begineers I didn't have much knowledge about Data Science but this course gave me some of the basic ideas behind data science which is really helpful .Take this course before enrolling into any data science courses.

автор: Sumanta K P

22 авг. 2017 г.

I got an overall idea that what I need to do before jumping into the bigger topics or even starting the real data science course. This is truely very important because people who don't have any idea about this topic needs to get an overview first.

автор: Abhijeet M

21 мая 2020 г.

Although the course structure is well designed, I would request the course designers to reduce the pace of the robot voice as she speaks very fast and an Indian I was struggling very hard to cope up with the speed. Please this is a humble request

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: Pablo G d S

17 мая 2021 г.

O curso é muito bom. Para alguns pode ser que seja de dificil aprendizado, devido a o fato de ser um robô. Para mim não fez a menor diferença, uma vez que o conteudo era de excelente qualidade. Obrigado pela oportunidade John Hopkins University.

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