I would like to thank Coursera team for providing such a good opportunity specifically the mentors of JHU, for sharing excellent video lectures. I would recommend my friends, colleagues, and juniors about this course, who is having keen interest to grow into the field of data science. Looking forward to complete the upcoming series of sessions.

This was a great beginner course given that I had no previous experience with coding or R Programming. It went at a good pace, I could work on my own time, and I appreciated the option for both video and script. While it only taught basics, it provided websites and connections needed to continue my understanding of the data science community.

Course is not as time-intensive, however it contains a lot of important information and helps lay out solid foundation in data science. Information is presented in an easily digestible and engaging manner, including some fun references/easter eggs that help lighten the mood. Tutorials for software are also easy to follow. Highly recommended.

I really loved the presentation style. It cratered to all learning styles which I find to be essential for online coursework. The information was basic, but it never hurts to have a solid foundation before going to the next level. Since the next course really throws learners into the deep-end, this course is necessary to be ready to go.

Excellent. Easy to follow. Great practice quizzes after each section. Notes available as text or video option. Definitely feel prepared for the next courses in the specialization. Great overview of R in relation to version control and other systems. I learned at least 3 software platforms in this course including RStudio and GitHub.

Its a good Course. The Questions and Assignment were framed well to make us think. Although I do feel much more questions should be added to properly assess the level of expertise achieved from the course. Then you would also be able to grade the level of expertise achieved and this would help in stratifying students as per their needs.

This course is a kickstart to the further R-programming related courses. Those who want to learn R programming with strong basic on its background, then this course is the right choice. The course materials are too much easy to complete but easy to those who attentively listen to the lecture videos. Heading towards the next course now!

That was introduction to Data Science specialization. Not too valuable as independent cource, but basic for whole specialization. Speaker briefly informs us about purposes and specific of data scientist job, indicates common mistakes and review tools for data analisys. Narrator is pleasant, seems like he is professional in this field.

This course is a good, brief introduction to the foundational concepts of data science and some of the tools you can expect to use when doing data analysis with the R programming language. It's best suited to someone who intends to continue at least with the R Programming course that is also a part of this Data Science Specialization.

Great introduction to data science and the associated tools. As someone new to data science this course provided a simple, yet firm and comprehensive foundation for the rest of the courses in the data science specialization. Definitely worth doing this course if you are thinking of pursuing any endeavors in the field of data science.

I thought this was a very fun experience. It was easy to follow along and it didn't take up too much of my time to pick up some interesting concepts. Though I do recommend that you watch some videos on YouTube with explanations on Git and GitHub, because that will really help make version control systems so much more understandable!

First experience got me hooked. I love coursera. This course, even though an introduction taught me a lot and showed me an error of my ways in everyday life. One question in the 3rd Quiz was very confusing to answer. But that's about it. I hope the rest of the specialization carries on forward in a similar maybe even better pattern.

The course was completely new to me. But the step by step instructiona made it easy for me to complete the course succefully. Linking of R and GitHub is like a magic to me ,who is new to programming. The Video on Control Version is fantastic and can be helpful for even professors like me who give group projects to their students.

I think this course did gave me a full impression regarding data science and guided me how to install basic tools successfully. Also, I found that the help guide and links those are introduced during lecture are very helpful, such as "Github help" and discussion forum. I used them a lot when finishing the last peer view project.

This was an excellent course. I always wanted to know how to use GitHub and this course knocked it out of the park for that. Also learned how to set up R & Rstudio on Debian 10 vs. Windows and/or Mac. I'm a FOSS guy so this course provided sufficient guidance around how to build my Data Scientist toolbox on that platform. Nice!

A short introduction to the primary tools and concepts for data analysis with R. The lectures cover a fair range of topics from installing the software to experiment design and types of data analysis. Relevant and informative examples are provided for each section. All in all, the course is a wonderful introductory experience.

This is a great course to startup a Data Scientist journey. Learn how to setup the tools to be ready for R programming and the concept of data analysis. A minor negative comment is that the robot voice is really annoying sometimes, but it is well explained in the Welcome notes and videos. OVERALL, good course to be enrolled.

It was interesting, including the presentation itself in the sense of the automation of the generation of the course. I will probably copy that idea for my future courses, otherwise the content without major problems. It catches my attention that they do not explain or at least indicate how to install these tools with Linux.

No começo, tive que me acostumar com a linguagem apresentada nos videos. Logo em seguida ja compreendi o meu funcionamento no curso: assistir os video, ler o texto, anotar a estrutura e os pontos-chave, exercitar quando era necessario, e resolver as questoes. Com este ritmo consegui aprender o que o curso propoe. Agradeço.

I liked this course. The material that you learn was pretty basic, but the community helped you digest the more indepth concepts (I am new to RStudio and GitHub). What some people will find as a flaw, I liked the fact that I had to go and look for the answers online and it wasn't just given to me in the course notes/slides.

A great course that provides an informed and thorough introduction to data scient. The electronic voice does take a little time get used to, but I really liked that the text files and videos where directly connected. It felt like I was reviewing the work immediately after going through. I liked that.

Highly reccommend it.

This is an excellent introductory course for Data Science. I personally feel that, I should really have taken this course sooner. It is an excellent beginners course. I would like to say a big thank you to the mentors. This course helped to understand RStudio and GitHub in a way I have never understood before. Thank You!

This course has really helped me understand how to value peoples work and share what i think and share my work with others. The lectures are very good and helpful. From the knowledge i have arquired i view things differently, more like a data scientist and i am motivated to complete my specialisation as a data scientist.

Great course! Explains the details of what is in the content of the rest of the certificate while not being too detailed. Showed which classes will be related to the content of each part of the introduction. Did a great job of setting up all required tools for the the R programming course (which I am currently taking).

I loved the course - the different kinds of formats of presenting the information really helped me in choosing the medium in which I wanted to learn! Thank you to all instructors and the links to all the material provided. I loved Hilary's name analysis and Nate Silver's take on US elections - thanks so much once again!