Executive Summary: Do not spend time on this course if you have minimal common sense and have read at least one article on Data Science.

I finished the 11 week course "Machine Learning - Stanford University - by Andrew Ng" 2 months ago, which was such a great course! It kept me busy for about 20 days (at about 4-6 hours per day) and I learned so much!

This course "A Crash Course in Data Science - Johns Hopkins University" , Part of a 5-course series, the Executive Data Science Specialization, provided just some superficial obvious information, took me only 3 hours to complete and even this time I would could wasted time.

Finally coursera now starts to make courses smaller and smaller and them adding multiple of them up to "Specialization", so that at the end you have to pay much more to get a certain amount of information and course time. With this course they seem to have streched it to a new extreme. The price for the certificate for this superficial short mini course has reached the same price ($ 44) as what I payed for the extensive great Machine Learning course from Stanford University by Andrew Ng !

All the course content is too basic to bother with. It’s just a bunch of common sense and a few definitions of vocabulary words that can already be found on Wikipedia. There is typically one page of reading stating basic definitions and intuitive ideas followed by a 10-15 minute video reiterating those basic ideas. For example, there is an entire unit just to explain that a report on a data science experiment should be clearly written, avoid unnecessary detail, and have concise conclusions. There is a page of reading to list these as bullet points and a 14 minute video to repeat these points.

This course is a waste of time. Thankfully, it’s short and free.

Great to do if, you want to dive into data science or machine learning. It is a must do, if you have no idea of the rationale behind statistics and data science as well as the need for it.

A light overview about Data Science that can be really useful as a first time on this topic.

Great starting point for any experienced professional with no data science background to understand this growing in-demand field, its purpose, the various components that comprise data science, in addition to overall objectives and outcomes of data science. Allows you to evaluate how much further one would like to dive into the field respective of your personal or professional objectives.

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.

A LITTLE TOO THEORETICAL. THE INSTRUCTORS SEEM CHALLENGED TO PRESENT REAL LIFE EXAMPLES. Quoting favorite examples from historical pure play ideas (e.g. predicting heights of boys) are frankly a bit dated, not relevant for a business audience, and hint at real life incompetence of instructors. And what is with trying to promote books these guys have written?

This Course was ideal to provide an overview to People that are not experts in statistics and data. In the future I know now what Questions to ask if someone wants to Show off. Thank you also for good visualization and reading material during the Course.

The only reason this course is two stars is because the content could be useful to a beginner in the field. The course itself, however, is of poor quality with un-engaging video content and an unedited book with multiple sections that are clearly derived verbatim from the sub-par video lectures. It could be drastically improved with a little effort and would hopefully provide more value to learners with genuine interest.

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.

This course is the 2nd certificate course I've completed through Johns Hopkins and Coursera, and the content is always excellent. I suggest pausing the videos and take notes to grasp everything, and for reference if you're going to take other courses along this path. I am also going to complete the other Data Science certification offered by JHU

I was looking for a data science course which will enhance my skill and knowledge. This course from Jhons Hopkins University just right to learn about Data Science. The course structure is excellent and to the point.Trainers are excellent in the subject and explanation equally good. Thanks coursera for having this course.

A decent overview on data science with interesting tips and advise on how to conduct your research and experiment. Gives an outline of your research progress and knowledge on whether you are on the right track. Plus, nice insights to look into and encouraging to learn more about the field.

The course asks for students' inputs after quizzes ("Help us identify the right topics"). What is this for, as it seems odd to ask those taking an intro course what it should cover? Perhaps I'm missing something here.

The course was very informative and knowledge gained from Data science expertise is exceptional. I thank Johns Hopkins University for offering the course for Data science beginners.Thank you.

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!

Very nice way to get introduced to the world of data science. Thanks a lot!

Nice and well taught .There is really alot to learn

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.

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.