- Supervised Learning
- Artificial Neural Networks
- Applied Machine Learning
- Medical Science and Research
- Health Informatics
- Responsible AI
- Reinforcement Learning
- Healthcare Ethics
- Data Ethics
- Machine Learning
- Machine Learning Algorithms
- Health Care
Fundamentals of Machine Learning for Healthcare
Completed by Charlene Lee
October 24, 2020
14 hours (approximately)
Charlene Lee's account is verified. Coursera certifies their successful completion of Fundamentals of Machine Learning for Healthcare
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.
Skills you will gain
