- Model Evaluation
- Reinforcement Learning
- Responsible AI
- Convolutional Neural Networks
- Data Ethics
- Data Preprocessing
- Deep Learning
- Machine Learning Algorithms
- Artificial Neural Networks
- Healthcare Industry Knowledge
- Healthcare Ethics
- Machine Learning
Fundamentals of Machine Learning for Healthcare
Completed by Rebecca Bird
December 29, 2024
14 hours (approximately)
Rebecca Bird'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
