Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles.
This course is part of the AI in Healthcare Specialization
About this Course
What you will learn
Define important relationships between the fields of machine learning, biostatistics, and traditional computer programming.
Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation.
Learn important approaches for leveraging data to train, validate, and test machine learning models.
Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment.
Syllabus - What you will learn from this course
Why machine learning in healthcare?
Concepts and Principles of machine learning in healthcare part 1
Concepts and Principles of machine learning in healthcare part 2
Evaluation and Metrics for machine learning in healthcare
- 5 stars82.67%
- 4 stars14.80%
- 3 stars2.16%
- 2 stars0.36%
TOP REVIEWS FROM FUNDAMENTALS OF MACHINE LEARNING FOR HEALTHCARE
it is a really good course for learning ML but some of the videos are a bit hard to fully understand
Very useful and practical content for healthcare professionals wanting to learn about machine learning.
Interesting and well crafted, it is mostly at an introductory level, but accurate and with many details regarding how to apply ML to healthcare. Worth to follow.
Excellent introductory course to understand Machine Learning in the context of Healthcare delivery
About the AI in Healthcare Specialization
Frequently Asked Questions
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Is this activity accredited for Continuing Medical Education (CME)?
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