Sep 08, 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.
Apr 15, 2020
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
by Alina S T•
Sep 12, 2019
I took the same course 6 years ago and it was a little more challenging. It actually had coding assignments. and not only in R, but in Python and SQL too. That was a more complex "toolbox"...
by Anoop B•
May 03, 2020
The course was excellent however the robotic sound of the AI was a challenge. Once I overcame my inhibition to learn from an AI system, I started to like the course and learnt a lot from it.
by Yitong L•
Jun 09, 2019
This course missed some important step, for example, the git push which is not be cleared how to push and does not teach us the git pull as the REANDME.MD is not in the local repo initially.
by Ashish K•
Dec 09, 2018
Should spend a little more time explaining how interaction between Git and Github works. It is not very intuitive and requires revisiting the video as well as google search to understand it.
by Arjun S•
Aug 27, 2017
A very easy course, can be completed in 3-4 days at max. Having done R programming course first, this was a breeze taking a couple days. Good for people starting off with the specialization.
by Sander H•
Apr 25, 2017
What I like (so far) is that you have to search for information via internet and by practising your knowledge in GIT and GIThub you can discover what you have learned or what should improve.
Apr 26, 2017
Some detail of the Quiz and course project were not mentioned in those video courses, it made me have to google or find out the answer in other ways. But through this, I did learned more .
by Samiksha S•
Jun 29, 2020
Good course for beginners to data science world.
However some more application questions must be added in each section to acquaint the learners with a thorough knowledge and understanding.
by JUAN D M•
Oct 20, 2017
Describe aspectos básicos para la utilización de herramientas, tipo de preguntas y datos que debe manejar un científico de datos; es un buen abre bocas para el resto de la especialización.
by Léa F•
Jul 23, 2017
Good introduction, although the teacher spoke in a very low voice (it was sometimes hard/impossible to catch what he said) and some of the videos could have been a little more exhaustive.
by Zach D•
Sep 30, 2016
A nice slow intro to Coursera, but not a ton of actual content. Good to get your feet wet, but skippable if you are familiar with the basics of the toolbox or taking courses on Coursera.
by Huaxin W•
May 19, 2018
Very simple and easy-going. A good instruction to the very beginner of the data science and programming. If some topics could be discussed in a bit more details, I would more appreciate.
by Vivek I•
Dec 15, 2016
The Data Scientist's Toolbox is a good introduction into Data Science specialization and gives a glimpse of what can be expected from the other modules. Looking forward to other modules.
by Vojtěch K•
Feb 02, 2016
It is unfortunate that I was only able to audit this course and not take it for free without the Coursera certificate, as it is currently not possible for me to pay for the whole course.
by Ahmad A•
Apr 24, 2017
greet efforts to learn us about Data Scientist's Toolbox, thank you very much
just one comment, it's about the instructor talking speed .. it was too fast and was not easy to keep focus.
by Yatin M•
Oct 20, 2016
A gentle start to the 10-course data science specialization. Would not recommend taking the course just by itself. If you're planning on the specialization, it's a great way to easy in.
by William K•
Apr 10, 2018
This is a good introduction the tools, however I had some issues with Git Bash and Git Hub, which was nor really answered in the lectures, could update the lectures with a live example
by Nikhilendra M•
Aug 26, 2019
The final assignment was really helpful in implementing what we learnt through the course. Some more details on the integration between Remote & Local folders would have been helpful.
by Xavier C•
Jun 25, 2018
Havegreatexpectationfortherestofthecurriculum.Visual presentations could be substantially improved, including the audio volume. But in general, great start down the Data Science path!
by Rajanikant T•
Aug 31, 2017
This is just a basic overview into the world of data science. I would recommend only to the students just starting out in this field. Still, is a good course starting out. Have fun !!
by Fouzi T•
Aug 12, 2017
Thanks to Johns Hopkins University for this helpfull course. It helped me a lot to understand the fondamentals of what data science is and the bueatiful tools used by data scientists.
by Ximena V•
Jul 17, 2016
All excellent and a very good introduction. I wish I was able to get my quiz graded without having to pay just to see if I was learning. For the rest, I recommended for a great intro.
by Phattara S•
Apr 21, 2018
This course describes the overview and useful tools for doing data science with less details. The material only prepare you for taking the other courses in the specialization track.
by Felipe K H•
Apr 04, 2017
Overall the course is very good and well paced, but I believe it could be a bit more clear in the git and github lessons on how to push from your local repository to your remote one
by Stella L X T•
May 31, 2020
Not bad to start off with! It teaches installation of all the required things for starting off R (e.g. RStudio, GitHub), and gives a basic understanding of experimental design too.