Overview

Google, IBM & Meta Certificates – 40% Off

One plan covers every Professional Certificate on Coursera.

Artificial intelligence is transforming healthcare, but successful adoption requires more than understanding the technology. It demands the ability to evaluate AI tools, integrate them into clinical workflows, and use them responsibly to improve patient care. This course equips healthcare professionals with practical, non-technical knowledge to apply AI across diagnostics, patient monitoring, clinical operations, and digital transformation initiatives. Learners will explore how AI supports, rather than replaces, clinical judgment while improving efficiency, reducing administrative burden, and enabling data-driven decision-making. What makes this course unique is its strong focus on real-world clinical application instead of AI development or programming. Through case studies, workflow redesign exercises, hands-on activities, role plays, and a capstone project, learners will develop the confidence to assess AI use cases, manage organizational change, and address ethical, regulatory, and governance considerations. By the end of the course, learners will be prepared to identify high-impact AI opportunities, lead responsible digital transformation initiatives, and implement AI solutions that enhance patient outcomes while maintaining safety, transparency, and clinician accountability.

Syllabus

Clinical Challenges and the Role of AI in Healthcare

This module introduces common clinical and operational challenges in the healthcare industry and discusses how AI and digital technologies can help overcome these challenges. By taking a problem-solving approach, learners can analyze problems like diagnostic delays, administrative burden, and workflow inefficiencies, and understand where AI can help make a difference. The module also explains the use of AI as a clinical assistive technology, managing learners' expectations about what AI can and cannot do. By applying AI concepts to real-world clinical problems, learners establish a practical foundation for understanding the role of AI in today's healthcare delivery environment.

Applying AI Across Diagnostics, Patient Care, and Clinical Operations

This module is centered on the application of AI in the various areas of clinical diagnosis, patient care, and healthcare operations. The learners can understand the role of AI in clinical decision support, patient monitoring, and operational efficiency without the replacement of clinical judgment. The practical application of AI is demonstrated in this module through examples, which illustrate the interaction of clinicians and healthcare teams with AI systems, the interpretation of AI output, and the incorporation of AI output into healthcare operations.

Managing Digital Transformation and AI Adoption in Clinical Settings

This module examines the successful implementation of AI and digital technology in the clinical setting. The learners will examine the changes that need to occur in the organization and workflow to implement AI in the clinical setting. This module highlights the importance of change management and building trust among clinicians to implement AI in the clinical setting. By the end of the module, the learners will have gained insight into the implementation of AI-driven digital transformation in the clinical setting.

Ethical, Regulatory, and Responsible AI in Clinical Practice

This module covers the ethical, governance, and responsibility issues that are critical to the adoption of AI in a healthcare setting. The learners will explore the impact of issues such as bias, transparency, accountability, and patient trust on the adoption of AI in a healthcare setting. The module also covers the governance and risk management practices that will enable organizations to adopt AI in a responsible manner. At the end of this module, the learners will have the perspective to balance innovation with ethical and patient-centered care.