Machine Learning in Healthcare: Foundations and Applications

This concise, high-yield course introduces essential machine learning (ML) techniques through the lens of real-world healthcare challenges. This program is uniquely grounded in real-world clinical insight and cutting-edge innovation. The course is led by Dr. Ghaith Habboub, neurosurgeon at the Cleveland Clinic Spine Center, Director of Intelligent Spine Analytics, Director of Spine Research, and faculty at the Lerner College of Medicine. Dr. Habboub brings unmatched expertise from the operating room to the classroom. What sets this course apart even further is its exclusive interviews with leading experts in AI, quantum computing, and the future of healthcare. You'll gain insider perspectives from industry renowned pioneers shaping the next generation of medical technology. This course is ideal for: • Healthcare professionals (e.g., clinicians, nurses, administrators) looking to understand how AI and machine learning can enhance patient care and operational efficiency. • Data scientists and analysts working in or transitioning to the healthcare industry. • Students and researchers in fields like biomedical engineering, public health, or health informatics who want a practical introduction to ML in clinical contexts. • Healthcare innovators and tech entrepreneurs aiming to build or evaluate AI-driven healthcare solutions. Learners will explore the core principles of ML in healthcare, build foundational knowledge of key algorithms, see highlights of real-world clinical applications of AI, and delve into how machines "think" and learn from complex healthcare data, equipping them with insights into data-driven decision-making in clinical settings. Whether you're a clinician, researcher, or innovator, this course offers a rare opportunity to learn from the front lines of medicine and machine learning.