Weeks 1 through 4 of this course indicates a function of "teaching" the material and the theory of ETL processes and data models. However, week 5 is the practical use of these teachings with no examples on how to actually do this process outside of the dry speakings and videos of Dr. Kahn. Dr. Kahn's presentation and reading ability is on full display, but what is not on full display is how to actually do what he is describing. I feel it would be more beneficial on teaching these techniques and connecting the theory with application through practical quizzes at the end of week 1 through 4 instead of multiple choice quizzes. I also have issues with the quizzes that require an 80% to pass with only 6 questions where I had some answers marked "incorrect" when they weren't the "most correct" answer. This is not how the real world operates and definitely not how to teach a very practical subject matter. I have a BA in mathematics and have spent the last 10 years as a data analyst and taking this 6 course program to learn more about how to apply it to the healthcare field. I did not feel this course was well designed for coursera and clearly meant for an in-person classroom. I believe it would do the students taking this course to relook at how this topic is presented. Also, it is necessary to relook at the websites provided in all the videos. I have found a key website to be out of date on "Example: Transforming MIMIC Patient to OMOP Person Steps 1 and 2" video in the FINAL week. Having a student review 3 assignments is incredibly short sighted unless the final grade for ones own assignment is then averaged. Having a 3:1 grade:submitt just doesn't make sense. This course DESPERATELY needs to be re-evaluated. The meat is there but not the potatoes.

Authors do not give a damn about it, there are more water than in average PhD thesis and as many practical skills as chicken has teeth. There are bloopers in course video that no one bothered to reshoot. Course listeners must do tasks, that should be done in SQL, in R and custom JAVA soft (which produces xlsx as output) and submit answers in pptx (sic!) to be peer-reviewed. Due to peer-review and lack of course listeners it could be hard to meet deadlines (I submitted my final task 2 weeks ago with forum campaign “let’s unite and help each other to review” but sill lack reviewers.)

The only thing that is theirs and hardly available opensource is clinical models presentation but it is described in the same terms, but way shorter, in the two articles of one of the course authors.

Don't believe what coursera says

Coursera advertised the course as "at your own place" what a lie. After completing the course I had to pay another $100 just to wait for the final assignment to be marked to get my certificate.

The courses for the specialisation keep getting pushed back, so you have to shell out a subscription for another month while you wait for them to come out.

I've spent far more time paying just to wait than actually doing any of the course materials.

What a great course!! Kudos to the professor for being so detail oriented!! I learned a great deal about the clinical data models from this course!!

Teaching was excellent, but I feel that the peer reviewed feedback model for the final project may not be the most helpful since they're the only ones looking at your work (as opposed to an instructor). Additionally, there were quite a few typos in the quizzes

Material was presented fairly well for the most part. The lecture videos had some small editing errors which looked a bit unprofessional. The workload was also a bit unbalanced - there was very little structured hands-on training prior to the capstone project which can appear daunting at first.

First, I must say that this course was useful in the sense that I learned new concepts and processes, but I found several flaws. The instructor is not really engaging. The quizzes contained questions on issues never discussed in the course material (videos or readings), and some of them are ambiguous or have answers that can be different given the current state of the art, or are a matter of opinion more than a fact (for example, is SQL a difficult language to learn?); orientation to solve these themes-questions by individual work was not provided. Some parts of the course may be outdated. Also, files important to finish assignments (specifically, code for the module 5) are missing and could not be found. The final assignment is a peer-reviewed project, and one can see many posts in the forum, from peers waiting for their project to be evaluated; also, even though I agree that peer interaction and discussion is important, I think that review by an expert or instructor is essential to really get one's errors checked and corrected. I'm conscious that given the number of enrolled students and the open enrollment model, is nearly impossible to get all projects reviewed by an instructor, but I think that other final evaluation system should be considered.

Lot of information, very little programming actually. The information is repeated numerous times Programming/writing on the other hand is not explained clearly and should be repeated more.

Gives a great understanding of ETL and the surrounding concepts from Zero. I personally found that a little boring, but for a total newbie to data and computers this is a perfect course.

I really enjoyed the course.

Found very difficult to finish.

Very good course on the high-level overview of data mapping & data profiling, data quality dimensions & data quality measures, & it required prerequisite knowledge/learning of SQL (BigQuery). This course was informative & not easy. I learned a lot.

Good instructor who took time to explain and walked through each steps of the ETL process. Highly recommended.

very hands-on course

Great course.

Great!

An excellent course that provides great guidelines for clinical data models. There are plenty of exercises to cement each block of learning material.

Good course, but the video is a bit too long, split into shorter video course

Great course. Would be great if lecture slides can be provided.

Contenu très intéressant dans l'ensemble, découverte des bases publiques et des concepts construits autour de ces éléments de la connaissance. Cette formation serait parfaite si la présentation était plus claire, en tout cas pour un français, moins répétitive et plus approfondie sur certains points. Les perspectives en connaissance partagée et connaissance induite (ML) seraient à explorer.