(76 Reviews)
(48 Reviews)
MD
Aug 27, 2016
Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.
Great Job!
SJ
Sep 9, 2017
This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.
By Marcelo H G
•Jul 12, 2017
Too much Superficial. Too fewer quizes. More external videos about hadoop, python, spark, data lakes. More paradigms broken. Need to explain what is On premise, rent and cloud.
By Jouke A M
•Dec 7, 2018
Not very complete, also you need some knowledge of the field already otherwise you will be left in the dark at certain moments. Not a very consistent course. I expected better
By Prashant P
•Dec 22, 2015
Too theoretical, e.g, comparison between statistics and ML is not at all useful. Too many quizzes after very short classes and on topics of absolutely generic things.
By Brandon L
•Aug 1, 2016
Good intent but poor execution. Tries to summarize all the major topics but ends up delivering a totally disjointed, cut-and-paste experience with no real flow.
By Arno B
•May 4, 2017
very elementary. Takes approximately 2 hours to complete.
cannot continue with the in-dept material but have to wait until next week (and payment ofcourse).
By Nellai S
•Jul 2, 2017
At some places, one lesson had the text and the next lesson was redundant with part of the information on video. you could club them in one an
By Seth D
•Feb 9, 2022
Too simplistic for me but maybe just right for someone that has never taken a computer science course or used a computer before.
By Abdullah A M
•Oct 4, 2020
The teacher knows quite well, but not suitable for beginners. This course is for someone who is already an expert in this field.
By Ayush J
•Jul 4, 2020
This course was good but the way of information and there should me more lectures and more detail study notes for this
By Dhruv W
•Aug 10, 2020
The least interactive course to throw money at. The teachers used very conventional and un-interactive ways to teach.
By Iair M L S J
•Dec 26, 2015
too basic, the 4 courses of this specialization could be just one course.
By Pulkit N
•Apr 6, 2020
Was a very broad review than was expecting.Content covered is too less
By Hussain, C
•Oct 21, 2015
Very general course. Doesn't give much insight into data science.
By Deepak G
•Jun 28, 2016
Very short. Quality of the course is also not that good.
By Diego V
•Apr 16, 2021
too much lingo and words without clear definition.
By Eduardo R L
•Oct 7, 2016
1-week does not seem enough for a Crash Course
By Shafeeq I
•Jan 8, 2019
Not that engaging content. bit lengthy
By Carlos C
•Oct 5, 2015
This course is too short.
By Yousuf B
•Mar 10, 2017
Overly academic
By Boris L
•Oct 5, 2015
Very shallow
By Ahmed A S A
•May 24, 2020
Hard.
By Umar F
•Sep 6, 2023
My experience has been profoundly disappointing. Given the university's esteemed reputation, I held exceptionally high expectations for this course. Regrettably, those expectations were utterly shattered. ChatGPT can explain data science better than this course.
First and foremost, one of the glaring issues with this course is its accessibility—or rather, its lack thereof. The examples and explanations provided throughout the course seemed to cater exclusively to STEM students, leaving others, including myself, struggling to grasp the content. The course fails to bridge the gap between subject matter experts and those new to data science, rendering it impractical for a wider audience.
Moreover, this course appears to provide only the most rudimentary information on the topics it claims to cover. Such superficial coverage does a disservice to learners, as it fails to impart the depth of understanding necessary to work effectively in the field of data science. In essence, it provides a mere glimpse into these subjects, leaving students ill-equipped to tackle real-world challenges.
One of the more disappointing aspects of this course is its lack of visual learning aids. Visualizations and practical examples are essential tools for comprehending various concepts, yet they are noticeably absent.
Furthermore, it's astonishing how the instructors managed to render such a short course profoundly tedious. Rather than engaging and inspiring learners, the course structure and delivery made it an arduous task to maintain interest throughout the duration of the course.
In conclusion, "A Crash Course in Data Science" from Johns Hopkins University has been, without a doubt, a complete letdown. It falls egregiously short of the high standards I had anticipated. The course's exclusive approach, lack of depth, absence of visual aids, and uninspiring presentation have made it a regrettable waste of both time and money. I would strongly advise prospective students to explore alternative data science courses that offer a more comprehensive and engaging learning experience.
By Anastasios B
•Dec 26, 2021
Quite disappointed. While I expected a high-level summary, anybody who has done basic stats in school probably knows 90% of the superficial level of information in this course. Buzzwords like "neural networks" and "random forests" appear during the course, but without even a high-level explanation of what those are. The lectures are pretty low-quality in terms of content and presentation. The most informative portion would the comparison of Machine Learning to Traditional Stats. The quizzes are pretty simple (with some common sense you could probably pass a lot of them without going through the content of the course). Completed the course in one sitting, in about a third of the time estimated on the enrollment page.
By Devon M
•Jul 30, 2020
There is an error in a question in one quiz. I have tried selecting each answer multiple times, and the response still comes up wrong. This is preventing me from completing the course, and the certificate, which I need to complete for work.