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.

Fundamentals of Machine Learning for Healthcare
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Fundamentals of Machine Learning for Healthcare
This course is part of AI in Healthcare Specialization


Instructors: Matthew Lungren
40,215 already enrolled
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634 reviews
What you'll 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.
Skills you'll gain
- Generative Model Architectures
- Statistical Machine Learning
- Machine Learning Methods
- Artificial Intelligence and Machine Learning (AI/ML)
- Deep Learning
- Healthcare Industry Knowledge
- Healthcare Ethics
- Medical Science and Research
- Machine Learning Algorithms
- Responsible AI
- Supervised Learning
- Artificial Neural Networks
- Health Informatics
- Model Evaluation
- Model Training
- Data Ethics
- Machine Learning
- Reinforcement Learning
- Health Policy
- Applied Machine Learning
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Reviewed on Oct 7, 2020
An excellent course for professionals with healthcare background, specially for those who want to test the water before diving deep into AI in Healthcare.
Reviewed on Aug 31, 2023
Mathew and Serena are excellent. I enjoyed the module. The subject matter is very dense but made palatable by these two experts. Thanks and kudos to them!
Reviewed on Feb 24, 2024
I really enjoyed learning from this course . Helped me increasing my knowledge and clearing my ambiguities and misconceptions regarding the AI in healthcare.




