- Health Policy
- Data Preprocessing
- Deep Learning
- Artificial Intelligence and Machine Learning (AI/ML)
- Convolutional Neural Networks
- Responsible AI
- Machine Learning Algorithms
- Healthcare Ethics
- Applied Machine Learning
- Data Ethics
- Machine Learning
- Reinforcement Learning
Fundamentals of Machine Learning for Healthcare
Completed by Monisha Rajesh Kulkarni
June 22, 2021
14 hours (approximately)
Monisha Rajesh Kulkarni'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
