Schedule
Asynchronous
Delivery method
Online


0 credit hours
Credits awarded upon completion
Self-Paced
Progress at your own speed
29.75 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. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.
Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. In this second course, you’ll walk through multiple examples of prognostic tasks. You’ll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you’ll learn how to handle missing data, a key real-world challenge.
These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. This course focuses on tree-based machine learning, so a foundation in deep learning is not required for this course. However, a foundation in deep learning is highly recommended for course 1 and 3 of this specialization. You can gain a foundation in deep learning by taking the Deep Learning Specialization offered by deeplearning.ai and taught by Andrew Ng.
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 Predictive Modeling, Risk Modeling, Decision Tree Learning, Random Forest Algorithm, Data Manipulation, Statistical Analysis, Time Series Analysis and Forecasting, Feature Engineering, Deep Learning, Applied Machine Learning, Statistical Machine Learning, Regression Analysis, Machine Learning, Predictive Analytics, Data Analysis