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學生對 科罗拉多大学系统 提供的 Clinical Data Models and Data Quality Assessments 的評價和反饋

55 個評分


This course aims to teach the concepts of clinical data models and common data models. Upon completion of this course, learners will be able to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), differentiate between data models and articulate how each are used to support clinical care and data science, and create SQL statements in Google BigQuery to query the MIMIC3 clinical data model and the OMOP common data model....




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!!



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


1 - Clinical Data Models and Data Quality Assessments 的 19 個評論(共 19 個)

創建者 Edgar Q


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 I have found a key website to be out of date on "Example: Transforming MIMIC Patient to OMOP Person Steps 1 and 2" video in the FINAL week.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.

創建者 Kabakov B


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.

創建者 Nicholas S


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.

創建者 Murali K


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!!

創建者 Allison B


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

創建者 William H


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.

創建者 Jonathan H


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.

創建者 Mor K


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.



Found very difficult to finish.

創建者 Flora T M


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.

創建者 Vu T T T


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

創建者 Mimi D


I really enjoyed the course.

創建者 H H


very hands-on course

創建者 Angela B


Great course.

創建者 Juan P V



創建者 Fidel G


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

創建者 qianmengxiao


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

創建者 Ling C


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

創建者 M. B T


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.