Schedule
Asynchronous
Delivery method
Online


0 credit hours
Credits awarded upon completion
Self-Paced
Progress at your own speed
20.4 hours
Estimated learning time
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:
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 deeplearning.ai 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.
This Course is part of a program
You can only buy it along with program.
Schedule
Asynchronous
Delivery method
Online
Earn necessary number of credit hours for completing this content
Such as Deep Learning, Keras (Neural Network Library), Image Analysis, Magnetic Resonance Imaging, Computer Vision, Machine Learning Algorithms, Data Processing, Applied Machine Learning, Artificial Intelligence, Medical Imaging, Predictive Modeling, Radiology, Statistics, Data Validation, Probability & Statistics, Statistical Methods, Artificial Neural Networks, Machine Learning Methods, Tensorflow, Machine Learning