Отзывы учащихся о курсе Набор инструментальных средств для специалистов по обработке данных от партнера Университет Джонса Хопкинса

I got a brief understanding of R. Better something than nothing. The problem is, they need to update their lectures. This would be less confusing and more convenient for students.

I know it might be the future for training videos but had a hard time staying concentrated listening to a mono tone computer generated voice. The course content itself was good.

Make it more illustrative.. The examples are very less and not explained properly for beginner. Assignments should be more practical. There must be a tutor to clarify the query.

A good attempt to give introduction on basic Data Science tools though most videos end abruptly which spoils the seamless navigation experience. Maybe the team can work on this.

Good introduction, but the professor could have been more descriptive about how to use git/github. These are new concepts for people so it may be difficult to grasp right away.

Probably a good course if you aren't terribly familiar with GIT or some form of version control. It also helps to get all the tools in place to be ready for the other courses.

I understand the rationale for the auto-voiced videos, but I wasn't crazy about it. More importantly, I didn't understand why the text-only versions can't be used on an iPad.

Good outline but perhaps a bit slow going when a lot of people want to get into coding as quickly as possible- could some of the git instructions come further down the line?

The automated videos have seriously reduced the value for money for this course. With thousands of students, surely you can spend a bit more time making this presentable.

Good course for an absolute beginner, but much too light if you have any experience at all with data science or programming. Entire course completed in just a few hours.

It is a good intro course to get set up with everything you may need for future courses, but it's not necessary if you are already a little familiar with github and R.

The assignments were too simple to solve. Maybe 1 or 2 graded questions on Git/GitHub could have been added considering the importance of its usage in future courses.

I enjoyed the start up course and look forward to more, but am battling to figure out how to sign-up for the next step all roads seem to force me back to the Toolkit.

Nice to have a place to get all the tools setup but it's also harder to feel like it's worthwhile when there are no applications for any of the things we installed.

I think final assignment can be improved. For example, the assignment implies that you know how to generate a codebook.md and the video classes doesn't teach that.

For people that are new to Data Science this is a good intro, for people that might have some experience with R, statistics and ML in general this is way to basic.

The course is structured well, but I found it too elementary, I didn't learn anything new. So, If you know basics of Data Science and R. Kindly skip this course.

I think this course could be integrated into the other ones of the specialization, or, if it is meant to be just a course to get an overview, be free of charge.

Helps to get the initial environment setup for the Data Science specialization.

Certificate received after completing the course is not effective/useful at all.

No subtitle in French as announced

It would be great to have the power point bigger when reading

The guide for connecting Rstudio and GitHub needs to be updated

it could have been better if it was more hands-on learning, for instance I don't understand why did we learn CLI till now and how will I link it to my studies

Might be a good introduction for those completely new to computational tools, but not useful for those with any background in git or R. Can be safely skipped.

Good course about getting the basics for the Data Science specialization, but a bit overpriced, as the content is low, and can easily be done in 4-5 hours.

You don't really learn all that much, but then again I have experience with R and some data stuff already, so perhaps it'd be more useful for someone else.

It was a great start to data science but also students should have it in mind that the material presented in the course won't be enough to get through it.