Fundamentals of Machine Learning for Healthcare
Completed by Lisa Dyan Brockmeier
January 22, 2026
14 hours (approximately)
Lisa Dyan Brockmeier'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
- Category: Model Training
- Category: Deep Learning
- Category: Machine Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Artificial Neural Networks
- Category: Healthcare Ethics
- Category: Medical Science and Research
- Category: Statistical Machine Learning
- Category: Healthcare Industry Knowledge
- Category: Machine Learning Algorithms
- Category: Machine Learning Methods
- Category: Supervised Learning
