Chevron Left
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: 32,455
Рецензии: 6,924

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:

301–325 из 6,813 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

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:)

автор: Yian L

9 апр. 2020 г.

I like the instruction of connecting programming with Github. This is not taught in my other courses but being extra helpful for people who will work in the programming communities. The automated voice delivers contents efficiently.

автор: Hassan M S

28 мар. 2020 г.

The method of presenting the course is a dream come true for me! I am the type of person who can better learn by reading and always enjoyed the reading material of the course. A course containing solely the reading material is epic!

автор: Debinson C C

27 мая 2021 г.

Se presentan las herramientas básicas para una persona que desea trabajar con datos. La metodología permite avanzar en los temas pero teniendo la oportunidad de revisar su proceso de aprendizaje e identificar los errores cometidos.

автор: Joseph F

5 нояб. 2020 г.

This is a concise course for someone who has zero background in Data Science. Relevant supplementary readings were available and the samples used were really helpful. I enjoyed the learning process and I also loved the xkcd comics!

автор: TAN S C

8 июня 2020 г.

Great course for a beginner. Very interesting introduction of Data Scientist’s Toolbox for self-learner in R like me. This course really useful and do help to solve my problem in track changes and manage my code for time to time.

автор: Eugene K

24 апр. 2019 г.

This course is very comprehensive and if you watch the video and try and follow all the links to webpages, publications, etc. and then try to connect the dots you really have a great start in data science. Not to be missed. Thanks.

автор: Susan M

22 авг. 2017 г.

Great intro course, really enjoy the self paced schedule. As a busy professional, it is often hard to find time to commit to scheduled courses. I am very grateful for Coursera, and all of the universities, who make this possible!

автор: Becky I

28 авг. 2021 г.

I found this course very helpful. I am a grad student and taking this course helped build experience with technology including: github, R, and Rstudio. I plan on taking more courses within the series to further develop my skills.

автор: Robyn W

16 авг. 2020 г.

I came to start learning about R, and walked away with an understand of why I also need to learn R, Rstudio, Git, and Github. I'm grateful that this course taught me how to set all of that up, in preparation for the next course!


10 июня 2020 г.

The way of approaching and explaining the concept was really helpful for me.

Nice way of approaching the concepts and problem-solving skills.

The best part is that it shows a perfect example and explanation of ML and Data Science.

автор: Rachel H

17 мая 2020 г.

This is a concise and well-structured course for beginners of data science. I would recommend this new way of teaching (robotic voice hahaha) for other online lectures, as this is a new way to review and update course materials.

автор: Wayne W

23 мар. 2016 г.

A good overview. Set the expectations for what will happen in the rest of the Data Science classes. Gave a lot of good, basic information for people that are not familiar with git, GitHub, Rstudio, and basic Linux/Unix commands.

автор: Umberto M

9 февр. 2016 г.

Is a very nice course. Is very basic but exposes you to the tools most used in the trade. If you have any IT background you will not probably benefit that much, except in learning what kind of tools are relevant to data science.

автор: charan k C

17 февр. 2020 г.

This Course gives you the basic level of understanding of what is data science and its impacts on the market. You can know about Version Control and Tools like R - Studio. Overall as a beginner, i learnt a lot from this course.

автор: Ann T

28 июля 2016 г.

If you have a background in IT you should get through this pretty fast, but it's still a well structured course with useful support in getting the basic tools set-up before the rest of the course. Clear, concise & to the point.

автор: Ana C G d P

21 июня 2021 г.

Amei o curso, aprendi muito e tenho certeza de que este curso é apenas o começo para que possa alcançar meus objetivos.

Didático, ilustrativo, possui muitas informações e exercícios para que possamos aplicar nosso aprendizado.

автор: Simeon I

25 мар. 2021 г.

I enjoyed every lesson, I have done a couple of data science intros but believe I highly recommend getting your hands dirty with tools before you dive deep.

You learn how to cross the bridge before you get there on this course.

автор: Pooja D

8 июня 2016 г.

What an amazing course!!!!!!!!!

At first I skipped this and started R Programming. But then I thought let me just check it once and I am really grateful that I started this. I am looking forward to complete whole specialization

автор: João V P D

8 авг. 2020 г.

It's a good introduction course! As part of a specialization, it fulfills its role. For those who don't have experience with programming and data science, it's a great place to start and so go through the rest of the courses.

автор: Ishika G

22 авг. 2020 г.

As a beginner in Data Science, this course introduced me to various tools used and cleared various concepts. Lessons were easy to understand and use of AWS Polly made it more fun. I would highly reccomend taking this course.

автор: Xiaoyang C

22 апр. 2020 г.

The illustration is exhaustive , step by step teaching you how to set up R RStudio and GitHub. A really great foundation course for who is interesting in those software and may think of data analyst as a future professional.

автор: Diandian Y

6 мая 2019 г.

Got to know the big picture of what is data scientist and what they are doing; Set up the tools and account of git hub; the instructions of how to collaborate and share codes and views among co-workers are especially useful.