Learner Reviews & Feedback for The Data Scientist’s Toolbox by Johns Hopkins University
About the Course
questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual
introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in
the program like version control, markdown, git, GitHub, R, and RStudio.
(243 Reviews)
(1056 Reviews)
Top reviews
LR
Sep 7, 2017
It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
NB
Jun 2, 2017
Nice Course. Basics are very well taught in this course.Thank you JHU and Coursera for this course. I have decided to donate 10% of my first salary to coursera once I am complete this and get intern.
6651 - 6675 of 7,160 Reviews for The Data Scientist’s Toolbox
By leo0807
•Jul 3, 2019
I think maybe because I have computer science background, so I think this course is too easy.
By Nikita S
•Feb 2, 2018
I don't really think that this amount of information should exist as a whole separate course.
By Lucio C
•Aug 8, 2016
Good overview. But it is confusing for the first class when you have no idea about the topic.
By Bhupen P
•Jul 22, 2021
Need more practice in R programing, Github, commit, branching, adding text, making directory
By Maciej M
•Feb 18, 2018
some information was interesting but in general I don't think it was crucial for learning R.
By Benny B E
•Aug 1, 2017
If you don't know any thing about data science, good introduction, otherwise a wast of time.
By Yves-André G
•May 27, 2017
A very simple course, focussed on installing the correct tools on your computer to learn R.
By Migdonio G
•Feb 11, 2017
Too little material for 4 weeks. All this could've been written in a PDF instead of videos.
By Mark P
•Oct 11, 2020
the computer voice is very hard to handle.
low production value of the course in that part.
By Kapeesh
•Jul 26, 2020
Video lectures where TTS, not at all engaging. Thankfully, text material was well written.
By Shahrooz
•Jul 22, 2016
Overall the course content is good, but the power points are not engaging and interactive.
By Mantra B
•Jun 27, 2020
Very Basic level. A little difficult to stay focused without having an instructor around.
By Sadanand U
•Aug 19, 2018
Very basic, may be a bit more use cases on Git would have been useful. But that's just me
By Uian S
•Nov 23, 2017
Few content for an entire course. I think this one could be together with R Programming.
By Ali A F A N
•Apr 12, 2020
Wasn't as good as I expected, but still I learnt from it, I can say it's above average.
By Andreas L
•Dec 3, 2017
I am aware that this is the introduction to this topic but it was a bit long-drawn-out.
By Juan J E
•Oct 22, 2017
I was already familiar with some content. it was a good starting point for may training
By Craig G
•Jan 27, 2017
A good intro to the tools, but for anyone with prior programming experience unnecessary
By Debanjan D
•May 25, 2019
Okayish course. This course will give you an introduction in RStudio and Data Science.
By João P S
•Sep 7, 2017
Too few activities for the time allocated. I completed this course in 4 periods of 2h.
By Danyal B
•Jun 7, 2017
I think the project became very confusing since no examples were done in the lectures!
By Seçkin D
•May 20, 2016
I think this class is best for academic people. I did not find what i was looking for.
By kheman g
•Aug 5, 2020
This is a very basic of the course where I learned so much about the different tools.
By John Y
•Jul 8, 2017
This could be wrapped into one of the other courses since its just environment setup.
By R G
•Jan 17, 2017
Pretty simple, the Univ of Michigan Data Science with Python set the bar pretty high.