- Deep Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Convolutional Neural Networks
- Reinforcement Learning
- Applied Machine Learning
- Health Policy
- Artificial Neural Networks
- Data Ethics
- Healthcare Ethics
- Model Evaluation
- Machine Learning
- Healthcare Industry Knowledge
Fundamentals of Machine Learning for Healthcare
Completed by Franco De la torre Loyola
October 9, 2020
14 hours (approximately)
Franco De la torre Loyola'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
