- Health Policy
- Healthcare Ethics
- Healthcare Industry Knowledge
- Data Ethics
- Artificial Intelligence and Machine Learning (AI/ML)
- Model Evaluation
- Applied Machine Learning
- Responsible AI
- Artificial Neural Networks
- Convolutional Neural Networks
- Machine Learning Algorithms
- Deep Learning
Fundamentals of Machine Learning for Healthcare
Completed by Aprelia Yuphi Septiana
February 21, 2024
14 hours (approximately)
Aprelia Yuphi Septiana'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
