This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios. We cover 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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One of the tough and amazing course i have ever seen, The unique structure of LABs and Assignment and their grading procedures are remarkable.
Thanks to Coursera , ILLINOIS and Pro Jimeng Sun for such type of valuable courses
Knowledge about health data is useful. The course should be leveled as an intermieiate course although it is labeled as advanced level. Instruction in week 2, not very clear; you may need to read carefully to pass it.
usefull
The course material is well presented, good as an introduction, but I'm not the only one who had problems with poorly designed labs and homework in Jupyter.
Why do we practice Pytorch in the first place to eventually begin graded assignment like "here you have Pandas, use it to do this, this and that" and without informing that dataset is corrupted! So after hours of frustration you have to read the forums and then figure out how to solve it. There is no way to see the issue in a dataset with 600k records. The tasks don't seem difficult after doing them.
I know it's an advanced course, but why almost every academic course I took online is poorly delivered? I've used to have homework that doesn't cover learning material at all. But in case of online course there is no way to get feedback or help from colleagues.
The course scope is good and the ML-related material is well-explained but there are errors in tests and some parts of the content that are needed to take tests are available only in a book. The book chapters are supposed to be available for free via links from the course but they were not for me. Also, the programming tasks are not very good. Some topics are introduced before they are covered in lectures and the last two tasks are too similar to one another.
The lab portions are the source of this rating and the reason I decided to cancel / unenroll (too much time spent on poorly explained and buggy programming exercises) which is a shame considering that the lectures and material covered were great in establishing the healthcare context.
This course is in my opinion designed for people who already know how to do deep learning but want to do an application in health care.
The isn't a proper teaching for deep learning, just test to verify that you know what you are doing.
I have tried to do this course and everything I learned while doing the test was by doing my own research
Extremely poor assignment guide. Most of assignments have ambiguous instructions wasting a lot of time
It seems like nobody bothered to proofread the labs. :I
Great material. Poor support for labs!!!!
The content overall is good and the course has potential, but the developer lacks attention to detail in the programming assignments; the programming assignments are also repetitive. If you just want to understand a very high level of how to apply a DNN to a healthcare problem using PyTorch, this will get you started. Hopefully the next courses in this specialization are better.
This should not be on Coursera! The lab assignments are filled with errors. No one gets the results they ask.
There is no feedback from the course directors on the disscussionforum!!
Labs instructions need to be made clearer. Autograder can be improved with hints. This course requires PyTorch skills, you need some time to skill up before this course.
The assignments are not related to the course at all. No extra help or knowledge were given before we hit the training of python or pandas.
I hate this course
because it has so much programming
and I
want only quiz for this course.