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學生對 提供的 AI for Medical Diagnosis 的評價和反饋

1,643 個評分
357 條評論


AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine: - In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders. - In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis. - In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. As a learner, you will be set up for success in this program if you are already comfortable with some of the math and coding behind AI algorithms. You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by and taught by Andrew Ng. The demand for AI practitioners with the skills and knowledge to tackle the biggest issues in modern medicine is growing exponentially. Join us in this specialization and begin your journey toward building the future of healthcare....



It was a nice course. Though it covers basics. A follow-up advanced specilization can be made. Overall, it's sufficient for beginner for an engineer trying to learn application of AI for medical field


Throughout this course, I was able to understand the different medical and deep learning terminology used. Definitely a good course to understand the basic of image classification and segmentation!


276 - AI for Medical Diagnosis 的 300 個評論(共 357 個)

創建者 A V A


Very good course on applying AI for image-based medical diagnosis. Some things that could be improved are : 1. adding content relevant to using AI in non-image based diagnosis 2. could be made more comprehensive with more applications, exercises and theoretical content by extending course duration to a longer time

創建者 Amit P


The video segments could be made longer to incorporate more information on how the modeling is done. A lot of new information was thrust into the weekly exercises. It would be better if the weekly exercises were a test of what we had learnt. A great course on the whole, anyway. The instructor was very clear.

創建者 Mariathea D


This is an outstanding course. I am a physician and this has been very helpful in bridging the knowledge gap between what I learned in other deep learning courses and the unique situation of working with medical data. I would however appreciate a deeper dive into how to work with the DICOM format.

創建者 Vishnusai Y


Introduces the fundamentals of using AI for medical diagnoses. Concepts are clearly explained and the assignments are well framed. More lectures regarding subtle concepts like MRI Image registration and calculation of confidence interval would have made the course more interesting and comprehensive

創建者 Poh S C


The course serves as an introduction to AI applications on medical diagnosis. The assignments are easy. However, video lectures are missing some minor concepts that suddenly appear in the programming assignment. It is recommended to take this course after you took Deep Learning Specialization.

創建者 Johan T


Good course but, as often is the case, too much time was spent on fixing small errors in notebooks, such as using the "wrong" function (i.e. np.multiply doesn't work when * does due to the very specific setup of the exercise, even though they are both element-wise multiplication).

創建者 Vignesh S


A very well structured course that covers most of the practical design challenges of deep learning applications in healthcare sector. A good foundation for people who want to pursue a career as a Machine Learning Engineer for medical diagnosis and/or computer vision.

創建者 Endre S


Great course! Although the coding exercises focus more on lower level details of matrix manipulation, and not on the parts for selecting a model, building and training it. Most of the model related code is provided if form of utility code or as pretrained weights.

創建者 Hasti G



I enjoyed taking this course. It would be great if assignments could be debuged, I tried downloading the assignments to debug using vscode but some parts of the assignments(datasets or some functions) were not there to be downloaded.

Thank you

創建者 Chad H


This was a great course for getting a high-level understanding of AI's applications in medical diagnosis.

The only issue is that the assignments are auto-graded which, coupled with bugs, can make submitting assignments very frustrating.

創建者 Pierre G


Great but 1) all notebooks must be moved to Tensorflow 2 and Pytorch 2) it's not a Deep Learning course but a data course (for people who want to really understand the classification/Unet models, they need to study another DL course)

創建者 Denizhan E


Course data and related util files with reasonable explanations will make this course magnificent. I spent a lot of time figuring out differences while I try it in my local engine due to version differences.

創建者 Lee Z Y


Pleasant pacing, very clear and concise lecture material. I was really frustrated with the final assignment though. Would be nice if the grader gives something more instructive than correct/incorrect.



A good course to understand the use of Deep Learning and AI in Medical Diagnosis. In this course, you can understand different ways to segment and analyze the images of brain tumors and X-Rays.

創建者 Kiran C


Use cases selected were really nice, Videos should carry more detail technical aspects and could be bit more lengthy and Assignments should consider multiple options to solve given problem

創建者 Anditya A


too hard

too little explanation in the exercises,

definitely not for beginner,

this is an expert class course,

even an experienced student, who's familiar with tensorflow might struggle a bit

創建者 Pooja A


A good course with challenging assignments. However, the assignments could have been a little less self explanatory and should have triggered deeper and more individualistic thinking.

創建者 Stephan P C


The assignments are extremely simple; mostly just implementing an equation in Python. The rest of the notebooks are basically readings. Maybe give a little more coding practice.

創建者 Ameera A


The course is build in a way makes it easy to learn. I liked how the assignments had been built and the way of grading quizzes

I think we need a special course for U Net

創建者 Philip J S


Very abstracted and high level course, no "intution" presented compared to Machine Learning of Andrew Ng; Nevertheless, still a great course for AI in Healthcare

創建者 Chakkarapani V


This course is a good starter for applications on AI on medicine. I enjoyed. But I felt there can me little more explanations instead of a very short videos.

創建者 Soham T


The course content was great and all theoretical concepts were clearly explained but, the instructions in the programming assignments were a bit unclear.

創建者 Nikolaos N T


Getting the right code for week3 assignment was really time-consuming - still have not found what was the error giving me the standardize function

創建者 Ravi P B


Nice course to learn basics of machine learning as well as get your hands dirty with application of artificial intelligence to medical diagnosis.

創建者 Muhammed A


it's good, I expected it to be richer, but I guess there's no much development in that area to teach currently, I hope it will evolve with time