Good foundation concepts for what will be required in DS according to the instructors. Good start point and presents basic challenges to getting you set up for the rest of the certification. Other courses will be required for more breadth and depth of concepts. Very good introduction.

It is a nice course which smoothly familiarize a novice data science learner to the nature and tools of their job. Although I prefer it to be taught by a real instructor instead of a robot, apart from that everything was designed carefully to introduce data science toolbox to people.

Achei de grande valia, no meu caso, especificamente, por me colocar novamente em contato com a parte mais técnica da TI - venho desempenhando papéis gerenciais a algum tempo e tinha certo receio de alterar a configuração da minha máquina para ser um "laboratório" de ciência de dados.

Good course for begginers like me. All information is provided very simple and it's easy to understand. Also involves srudents not only looking videos but offer books. In addition you will need to search some information yourself to complete some tasks.

Thanks for this great course.

Even though it is a starter course to the specialization learned so many new things like amazon polly which is being used to generate these videos, R-markdown and how important is it to produce reproducible research.

A must take course for any data science aspirant

Happy Learning!!

It's a great course for beginners. I had little knowledge about data science. I didn't even know what was R and GIt. After taking this course, I had a preliminary understanding of them. If anyone wants to learn data science without any experience, this one can be your start point!

All the information felt applicable to my current role. The main thing I gained from this course is that I feel more confident in the tools at my disposal as a data analyst. Additionally I learned about tools I had never heard of & how to utilize them, and for that I'm thankful!

Great way to learn R and become familiar with how to use it. As a developer with an understanding of Python, Java, C and C++ I could quickly see how to use R, how to extend it and start working with it today. Very good use of supporting tools like Swirl to assist with teaching.

The course provides a good introduction to the necessary toolbox required. It provides introduction to the Rstudio interface and Github version control system. The course helped me gain a lot of knowledge regarding Data Scientist toolbox, especially the version control system.

I found this course to be effective at getting the student to recognize the baseline set of tools, skills and behaviors expected in courses 2-10. Moreover, none of said tools, skills or behaviors fall outside the confines of typical and/or "in demand" experience. Nice work!

Great course to get started with data science using R as primary language. Good data practices are encouraged and use of GitHub for version control gives additional confidence to anyone wishing to preserve their work that leads them up to the solution to the problem at hand.

It's an excellent introductory course for the specialization, I have recommended this course to a friend because I have found the content pretty useful. I will continue with the other courses of the specialization and I'm very grateful to have this opportunity from Coursera.

This is a nice course and well taught by all facilities made available by the facilitators. As soon as am financially able to start to finish from where I stopped, I will activate my remaining course left to roundup Data Science Specialization.

I really appreciate. Thank you.

Basic course introducing the minimum tools to start your journey in data science. The course was very important for me to get up to speed with Git and GitHub. All the information was given in a concise and objective way, yet covered all basic important points of such tools.

Might look trivial at first glance to more experienced users, but was very much essential for a complete beginner like me. Gives a nice overview of a somewhat overwhelming (and sometimes intimidating) field and equips you with the basic tools necessary (like how to use git).

The "Data Scientist's Toolbox" offered by Johns Hopkins University is a good head start for the newbies in the field of Data Science. The course gives the brief introduction to various software used by a Data Scientist that is R, R studio, Git hub and Git (version control).

Very good introduction to data science. It gives a general overview on data and its problematics but also tips and help on how to start with the basic tools that will be needed (I haven't done any R programming and didn't have a github account so that was helpful for me).

It is a very good course to get introduced to the world of data science. Working knowledge of R, RStudio and GitHub is covered in a very nice and organised manner. I feel more confident and equipped to proceed further and learn how to solve problems through data science.

Интересно было посмотреть как работает один из лучших исследовательских университетов мира.

Кроме настройки программного обеспечения много узнал об основных принципах науки о данных.

Очень понравился пример с Хилари Клинтон. Возможно это был роковой момент в её поражении.

This is not a coding course. It is a course to bring you up to date with the logistics of using R: downloading packages, using RStudio, using GitHub version control, and familiarizing oneself with the overarching concepts of experimental design, statistics and big data.

A very easy to understand, nice and simple course. ample quizzes and puzzles available. A recommendation : please include a thing or two about RStudio Cloud. Especially, please include how to tie up your github repo to RStudio Cloud; as the procedure s different for it.

It's really enjoyable, a lot to know and a lot to discuss. The other links provided for more details are very much helpful. The feature of the discussion form is very helpful. Thanks, to Coursera and the team of Coursera for your high great work to open this platform.

Muy buen curso introductorio en el que se pueden observar las herramientas necesarias para realizar análisis de datos, además de que muestran quienes son Científicos de Datos en la actualidad y qué tipo de análisis realizan, todo adquiriendo la información de internet.

Setting up the environment is often the tricky part that deters people from moving into, or back into coding. This class provided me with a hand-holding needed to start coding again. I recommend this course as a kick starter for those who were on legacy environments.

What a great introduction. It needs a lot of reading and self developing to be able to do that project at the end. It's kind of difficult but you'll feel that you've really learned something that will be useful for the rest of your life. Thanks JH and Coursera staff.