About this Course
AI is transforming healthcare, offering new ways to improve diagnostics, personalize treatment, and streamline clinical workflows. In this course, you will explore why AI is essential in modern healthcare, examining how data—ranging from electronic health records to medical imaging—drives AI-powered solutions. You’ll be introduced to key data exploration techniques used to uncover patterns and insights in healthcare data, as well as foundational AI approaches, including traditional rule-based systems, predictive analytics, and emerging generative AI models. We’ll also discuss the challenges of AI in healthcare, including biases, ethical concerns, and AI ‘hallucinations’—instances where AI generates misleading or incorrect information. By the end of this course, you’ll have a solid understanding of AI’s capabilities and limitations in healthcare and be prepared to critically assess its role in patient care and decision-making
What You'll Learn
- Explain the role of healthcare data in AI-driven solutions
- Apply basic data exploration techniques to healthcare datasets
- Differentiate between rule-based, predictive, and generative AI approaches
- Analyze ethical challenges, bias, and AI hallucinations in healthcare
Prerequisites
- Basic computer and internet skills
- Ability to follow course materials in English
Instructors
Eugene Tunik