Overall, the information in the course was useful. However, the videos in most modules were very short and could have been combined into more logical segments. The assessments were often disconnected from the actual material covered, meaning that questions were asked about topics that had not been discussed. The assessments needs to be reworked to reflect the actual content taught OR the modules need to be more fully developed to cover the content of the assessments.

Very clear and well-organized course. I have learned quite a bit about the different types of clinical data, why they are important, and how to transfer them to analytical useable data sets.

Good introductory course covering key features of the various data that are gathered or used in health care. No prior knowledge about the topic is required.

Examples are narrow and give the appearance of snippets rather than instruction. Course not well aligned,

Main lecturer was difficult to understand -- I needed to spend time going back over and over on transcript of lecture and change the sentence structure on my notes to be able to comprehend. It was a rather disheartening experience

There was some interesting information in this course but it was too basic and stayed too basic. Really, if you added up all the 1 and 2 minute videos for any given week, you wouldn't even get a single good lecture out of it.

The course is well organized and information dense - very efficient and very clearly explained. Highly recommend for a solid overview of clinical data in healthcare.

Videos are too short, some are just seconds long. The videos were not informative enough. There is one presenter that speaks so fast that you can't understand what he is saying. I would have liked more practice examples.

It has been a great course that obligued to me to work hard snd read too much because I am an Electronics with some self study programs in Medical field that open to me the path to go to AI in Healthcare Specialization programs run by Stanford University School of Medicine, the greatest one.

All the study material and tools are excellent. But first class as a top lectures the Highly Professional professors of the Stanford University with whom I took a contact in a weekly time.

I expect to continuo with the program till I become conversant to get my AI Healthcare Specialization. Thank you very much. I will highly recommend your online programs in Medical Field to all of my friends.

It would be helpful to be able to see all items that need to be completed. I took the final test and it says I've only completed 2 of 5 courses.

Nicely Framed and Executed in a simple language so anyone can catch up earliest.

Really dislike that you do not show the correct answer and explain why an answer is incorrect.

Module 7 was just theory. Better intuitive examples can be given in all the modules.

I felt it is a bit offsetting and boring, exams and quizzes are quite difficult, It can be better. Thank you!

where is my certificate????????

Questions are debatable.

Great introduction and overview of how medical ethics, medical data, clinical trials, and other non-standard data can play into the formation of ML workflow and pipeline towards generating algorithms that can give health insights, and feed into improving patient care. Approaches to forming appropriate research questions related to types analysis and patient data is valuable for those who are migrating into Health AI from other fields.

This was the best course I have taken online. A lot of very complex concepts and topics in healthcare data processing were discussed. Best thing I loved about this course was very concept was broken into easy to understand short vedios and presentations followed by a knowledge test. This gives a proper view into what an advanced level course would look like too.

Solid knowledge about how to work with clinical data, covering all important differences as compared to typical data science tasks. For me the most useful concepts were: dealing with unstructured data (esp. clinical text), knowledge graphs and electronic phenotyping.

The course program is very intuitive and challenging. Overall, it is a very good course and I will recommend it to anyone interested in understanding clinical data, in particular for data scientists.