Learner Reviews & Feedback for The Data Scientist’s Toolbox by Johns Hopkins University
About the Course
(243 Reviews)
(1056 Reviews)
Top reviews
SF
Apr 14, 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.
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.
6351 - 6375 of 7,125 Reviews for The Data Scientist’s Toolbox
By Sk A A
•Jul 10, 2019
Nice
By Jacob C N
•Mar 23, 2019
Good
By Ruben K
•Nov 28, 2018
cool
By shiva s
•Sep 1, 2018
nice
By Anup K M
•Aug 22, 2018
good
By Alessandro D B T
•Apr 29, 2018
Good
By Tiange X
•Jul 13, 2017
good
By dragie
•Apr 5, 2017
good
By Rose S
•Nov 23, 2016
Good
By Chinmoy D
•Nov 5, 2016
Good
By Andika
•Apr 30, 2016
Good
By Harsha G
•Mar 3, 2016
good
By liyp
•Dec 8, 2017
完成了
By MINHAJUL I
•Jul 19, 2021
..
By Abdul J B A H
•Oct 15, 2020
ok
By Cabes M
•Dec 31, 2016
df
By Aditi D
•Nov 15, 2022
-
By Myriam G
•May 25, 2018
-
By Matthias M
•May 20, 2018
V
By Grant S
•Apr 14, 2017
J
By Andrew D H W
•Feb 15, 2017
G
By Mununur M
•Sep 13, 2016
I
By Sudheer K
•Jan 29, 2016
G
By Nick B
•May 5, 2019
Hi guys. I'm not sure that you are reading the feedback, but instead of saying that it's good or bad I'm going to come up with suggestion. I'm data pipeline architect with 20+ years of experience who decided to take these courses to understand a gap of knowledge that current data scientists have. I think it comes from the very course. The R is kind of out dated for current world of big data, but I think you've already heard about this. Some Data Scientists who show up in our company they are good with theory but very bad in implementation. They don't understand the Big Data, especially distributed data. R is good language to the lessons but it doesn't have any connection with real world. You better include some basic knowledge about Spark (especially Spark ML), distributed computation and finish with R. Most of data science algorithms and libraries implemented (and used by real world) are in Python. Contact with some Cloud Providers like AWS and Google to create accounts for education. You course would be more attractive and, what is most important, would be more useful for people and companies where they start to work.
If you want, you can contact with me about some volontier consultancy. My email is nick.orka@gmail.com
By Matthew W
•Aug 10, 2018
Generally good information, but the static powerpoint videos are a bit too vague to be useful. I ran into issues several times when the steps described in the video (sometimes providing incomplete terminal or git commands) didn't coincide with the steps described in site specific tutorial videos recommended in the course forum. So I ended up spending a lot of time 1) figuring out the full commands required, and 2) reconciling conflicting sets of instructions after receiving error messages. This mainly occurred when trying to get my local git work to correspond to GitHub. I suggest more actual demos in the video lessons (i.e., actually type in full commands, show the result, and explain how to interpret those results), or 2) explain overarching concepts and then simply list a set of existing online tutorials that should be followed.