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Home » Content news » Cleveland Clinic joins Coursera to teach the latest healthcare skills at a global scale
Cleveland Clinic joins Coursera to teach the latest healthcare skills at a global scale
By
Marni Baker Stein
Chief Content Officer
January 19, 2026
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Today, I’m proud to welcome Cleveland Clinic, one of the world’s largest and top-ranked health systems, to Coursera. 
This collaboration comes at a timely moment. As demand for healthcare workers continues to rise, the World Health Organization projects a global shortfall of 11 million healthcare workers by 2030. At the same time, GenAI is transforming the industry, with 85% of healthcare organizations exploring or adopting GenAI.
To help address this, Cleveland Clinic is launching two courses focused on applying in-demand technical skills in healthcare.
Machine Learning in Healthcare: Foundations and Applications
Beginner level · 3 hours to complete
Skills you’ll build: Emerging Technologies, Reinforcement Learning, Clinical Experience, Supervised Learning, Healthcare Industry Knowledge, Machine Learning Algorithms, Health Informatics
This course is taught by Ghaith Habboub, MD, a neurosurgeon and faculty member at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. It combines foundational principles with real-world perspectives from healthcare and AI experts to help clinicians, data scientists, and researchers learn how to apply AI in clinical settings.
The course focuses on three core areas:
Core principles of machine learning in healthcare.
Real-world healthcare processes that can be automated using AI algorithms.
How AI models solutions can support clinical expertise to foster innovation, enhance efficiency, and improve patient outcomes.
Computer Vision and Sequence Analysis in Machine Learning
Intermediate level · 2 weeks to complete
Skills you’ll build: Transfer Learning, Applied Machine Learning, Data Structures, Convolutional Neural Networks, Model Evaluation, Health Informatics, Predictive Modeling, Biomedical Engineering
Dr. Habboub, an expert in medical technology, explains how to use machine learning techniques to analyze medical images and apply time-series data analysis through hands-on projects. Learners will design models to analyze MRIs to detect tumors and analyze vital signs to predict clinical events.
The course teaches how to:
Build and optimize convolutional neural networks (CNNs) for medical image classification and segmentation.
Apply transfer learning to improve AI model performance even when working with limited datasets.
Utilize sequence analysis to identify critical state transitions and patterns.
Amid a growing need to train healthcare professionals, this new collaboration helps learners gain the latest skills needed to support patients and communities around the world. We’re honored to have Cleveland Clinic join leading healthcare innovators on Coursera, including Johns Hopkins University, Yale University, Moderna, and Novartis. Collectively, healthcare content on Coursera has already reached 14 million learners.
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