- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Model Evaluation
- Health Policy
- Responsible AI
- Data Ethics
- Healthcare Ethics
- Artificial Neural Networks
- Deep Learning
- Machine Learning Algorithms
- Machine Learning
- Reinforcement Learning
Fundamentals of Machine Learning for Healthcare
Completed by Guus Bernardus Spenkelink
September 14, 2022
14 hours (approximately)
Guus Bernardus Spenkelink'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
