If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by deeplearning.ai and taught by Andrew Ng. 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.
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. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. 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. 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 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders.
This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in 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. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments.
AI is transforming the practice of medicine.
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