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.
KM
harsh, but with 2 years of experience i could do it fast
SS
I really satisfied with methodology of this course. and i am so excited for the completion of whole specialization. Thank you coursera, illinois team and Pro Jimen Sun for such wonderful opportunity
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I really satisfied with methodology of this course. and i am so excited for the completion of whole specialization.
Thank you coursera, illinois team and Pro Jimen Sun for such wonderful opportunity
harsh, but with 2 years of experience i could do it fast
The material is fascinating & timely and the instructor is clearly a deeply versed expert who has a passion for explaining things. The reason this is a 3/5 is that the labs / assignments are oftentimes poorly written and do not match the lectures. There are significant typos in the assignment / labs. The in-notebook "check your work" cells and the notebook graders following submission do not give much guidance or clarity on what to do when something is wrong. Much of my time spent was trying to learn Pytorch concepts that could have been explained far more clearly. I don't mind doing hard work if it advances my understanding of the material (e.g. data cleanup requiring an understanding of the data, a really gnarly model architecture, etc) but I felt much of my work wound up being documentation reading that had little to do with making sure I understood either the healthcare side or the deep learning side.
There is neither much of learning nor learning flow. I almost gave up on this specialization. Maybe my expectations were too high. I've done many courses online and this one definitely won't be my favorite, or maybe Healthcare isn't my topic of interest at all so I see this course from a wrong perspective.
I'm a Tensorflow guy not Pytorch and homework is mostly brute-forcing the tasks to fit the goal eventually forgetting what you are doing. Maybe I'm dumb on such things? Maybe my review would be better if I knew how to work with Pytorch before taking this specialization. People say that Pytorch is much easier than Tensorflow but here I see it more frustrating and counterintuitive.
Really tough material, but I definitely learned alot. Be prepared to Google and read the Pytorch documentation.
Autograder is working fine but this course requires PyTorch intermediate skills to succeed