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

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


Instructors: Matthew Lungren
38,543 already enrolled
625 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
- Data Ethics
- Artificial Neural Networks
- Healthcare Ethics
- Machine Learning Algorithms
- Health Policy
- Model Evaluation
- Artificial Intelligence and Machine Learning (AI/ML)
- Convolutional Neural Networks
- Applied Machine Learning
- Responsible AI
- Data Preprocessing
- Machine Learning
- Reinforcement Learning
- Healthcare Industry Knowledge
- Deep Learning
Details to know

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Reviewed on Nov 12, 2020
Completing this course has given me a solid foundation and confidence to engage at a deeper level with AIML in health, both as a student and exponent thereof.
Reviewed on Sep 9, 2020
Amazing course teaching the innumerous opportunities in the healthcare sector and the application of AI in the same. Beautifully drafted course with intriguing tutorials and exercises.
Reviewed on Oct 8, 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.

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