Covers all the basics. But yeah, just the very basics. Leaves a lot more to be learnt. I'm sure the upcoming courses in the specialization would be helpful

It was good - I think I would like a bit more on Github, but it gets covered in other courses. It shall have more material on the coverage of data science.

The introduction was very precise and straight to the core concepts of data science.

Please include a slide with the road map of becoming a data scientist.

Its a good basis. But i think there is a lot of information that is not relevant . Also, the materials of some questions are not mentioned in the videos.

It is good as a start for a beginner, but I do not think it is adequate to be a separate course. Much of the material can be easily addressed in one week.

It's a great course to have very basic introduction of Data Science.

In the meanwhile, also teach us how to install the necessary tool for future purpose.

Not the most engaging material, but the course does a good job of covering the fundamentals of R and GitHub and helps you download the necessary software.

Some typos in the slides need correction. Narration can be made more lively. Slides still quite classical in format and may be improved for better impact.

Good overview of Data Science, but geared more towards people who have little background in computer science. Info that *was* presented was very thorough.

Auto-generated voice is a major down-point. Then this is supposed to be a beigner friendly course, but it isnt really looks like that in certain aspects.

It's a really good course for the absolute beginners, but for me it was quite slow. I just took this course because it is the part of the specialization.

There are a lot of info on the video. Would be good to share a copy of the slides for the Git links/instructions so we can use them as a reference later.

This lecture tells you a lot about new places for experiment and study such as github, r studio. Hope many people check out this lecture and gain a lot!

This course provide a good introduction to github , Rstudio and command line interface.

it also gives a information about different ways to analyse data.

Basic introduction to the tools that will be adopted in the Data Science. I do hope there would be more information regarding Hadoop, Python, SQL, etc.

As it is a very technical to set everything and to start working on it but the mentor have tried to make it easy. For a beginor it can be challenging.

Informative, but course did not provide exact information needed to complete the assignment without additional research (unless that was the purpose).

Although I am vey much satisfied with this course but i felt a little low during the slides for explanation of types of data science .

Rest was superb.

Pretty light weight so far, but I certainly understand it's targeted at a broad range of people so the vanilla material is probably a chore for some.

This is a clear introductory course, but the content is not as much as expected. Compared with other coursera course, this one is like one-week pack.

The course is well structured but I still prefer that students new to this must read from other sources as well to completely understand the topics.

Good and easy introductory course. Finished it in about 3 hours total - don't expect this to be the pace for the rest of the specialization, though!

Lots of information. I learned quite a lot. It was a nice and informative introduction to Data Science in all aspects technically and theoretically.

Interesante introducción, quedas con el entorno listo para iniciar el aprendizaje. Se hecha un poco de menos un humano en las clases pero está bien

This is a mere course on installing all the necessary tools and setting your environment, so the explanations are short lived and practice is null.