Machine Learning for Medical Data
Completed by Umed A Ajani
September 14, 2026
10 hours (approximately)
Umed A Ajani's account is verified. Coursera certifies their successful completion of Machine Learning for Medical Data
What you will learn
Define supervised and unsupervised machine learning techniques used for healthcare datasets.
Apply preprocessing, feature engineering, and class-imbalance management techniques to real healthcare datasets.
Design and implement supervised learning models for disease prediction and clinical decision support tasks.
Evaluate model performance using precision-recall metrics, calibration, and external validation.
Skills you will gain
- Category: Convolutional Neural Networks
- Category: Machine Learning Algorithms
- Category: Healthcare Ethics
- Category: Model Evaluation
- Category: Machine Learning Methods
- Category: Machine Learning
- Category: Data Preprocessing
- Category: Recurrent Neural Networks (RNNs)
- Category: AI Personalization
- Category: Electronic Medical Record System
- Category: Data Analysis
- Category: Predictive Modeling
