- Convolutional Neural Networks
- Health Policy
- Reinforcement Learning
- Responsible AI
- Model Evaluation
- Data Preprocessing
- Artificial Intelligence and Machine Learning (AI/ML)
- Artificial Neural Networks
- Healthcare Ethics
- Machine Learning Algorithms
- Data Ethics
- Machine Learning
Fundamentals of Machine Learning for Healthcare
Completed by Arian Farokh
September 4, 2021
14 hours (approximately)
Arian Farokh'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
