This course covers deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.
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Very good course with hands-on practice of the different course material. If you're interested in using Deep learning methods for Healthcare, this is a good starting point, and from the different notebooks and course materials you do you own research and try to build more knowledge. For a university course it is quite easy though, I would not agree on the advanced level, but a good starting point as their isn't much equivalent online.
I rated high number, which is 4, because this is the only deep learning course related to EHR data and I appreciate your start journey. From other courses delivered in coursera, especially in "deeplearning.AI", I viewed as positive is to include lab. You tried to include lab, but your question does not motivate/encourage for new comer to the course. I would recommend you to include in your lab to write/include some code in the middle of the questions, you have to support learner to keep working (including a lot of codes in the middle encouraged learner to keep doing their assignment and loves the coding). Please include more additional lab works and the lab works should include answered codes in the middle to encourage learners. I hope this supports you.
I think it's a good addition to two previous courses in specialization.
It's short and sometimes the lecturer tries to explain too many things at once. It's not a course to learn things from scratch, furthermore it would be difficult to apply knowledge from notebooks elsewhere if you aren't experienced. I wish about an assignment about GNN / GANS / VAE, all these things are interesting but only briefly covered.
I've never heard of Graph Neural Network. Well, every neural network actually is a graph, didn't know it's a separate kind of network.
Some exercices are not well describe and the efficiency of "autograd" is really poor. So you must send your work without knowing if you are in the good direction and you only have 5 tries...
Also, nobody answer you when you're stuck somewhere, the staff team seems to be inexistant.
Course lecture videos give good conceptual overview, but it was very difficult to connect these concepts to the homework assignments. I spent much longer than the recommended time on the assignments as there was little support from the course instructors. Wouldn't recommend this course to a friend.
homeworks and course chapters unrelated to each other. The questions or how to solve them is never taugh in lectures. You need to study outside of the course because it doesnt give you the necessary information
Lab instructions and support non-existent! Beware