Learner Reviews & Feedback for The Data Scientist’s Toolbox by Johns Hopkins University

The content is very basic. The whole course took my around 6 hours to finish. I think the instructor should add more solid training on GitHub.

Estudar com essa inteligência artificial falando é IMPOSSÍVEL. E o material escrito só está disponível em inglês. Isso desvalorizou o curso.

A bit odd this one. It hase some points, but most of the training is looking on what the other courses are.. Like paying for commercial :-)

The course was just fine, but I don't think we should spent entire 4 weeks on it. One or two week for this course would be better I think.

This course is very basic for a person with an IT background, but nevertheless might come in handy for people without relevant experience.

G​ood overview intro, but assignments only measured that you were listening, they did not require applying content to any new challenges.

Difficult to follow the robotic voice at a speed of 1,5; the links simply don't workAnd, known bugs on LaTeX need to be found by googling

There is a slight lack of clarity in videos in terms of audio and also in terms of what exactly the author/lecturer is trying to convey.

thank you for the course it was useful. However the machine voice is really annoying and make fell uncomfortable and unfocused all time

Course content meets the standard. However, the computer voice is really terrible. I suggest you switch back to human voice teaching.

It's a very basic course and easy to get through. I wish that they wouldn't make you wait to get to the next section of this series.

Gives a good overview of topics and the specialisation, however is still very basic. I'm looking forward to the next advanced courses

Some of the information for this course seemed to be missing and I felt I had to either guess a lot or search the internet for help.

Good as just an introduction to data science. Some more exercises using Github, maybe some collaborative works would have been nice.

The "robot voice" speaks really fast making me having trouble to understand the content several times. Overall it's a great course.

gives some good information but the git section isn't really well made and it could have some improvements on sound and quality

Very basic overview of the tools and installation of them. Should be an optional course rather than part of the specialization.

Peer-review assignment questions leave out some assumptions; it took me a while to figure out what exactly was expected of me.

This course was a beginner level course and the difficulty level was quite low and in depth detail should have been provided.

Extremely basic, should likely be a pre-req for non CS/IT types but could easily be summarized for more experienced students.

It is a good introductory course, but it could be optional for people with some experience in the field, as it is very basic.

The real basics of data analysis. The course is not bad I would just say it may be too simple even for an introductory course

Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.

This is a good introductory course to some of the tools but it doesn't go into the details of R programming or Data Science.

не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации