Title: Applications of AI in Healthcare

Location: US

Company: Hamad Bin Khalifa University

About this course:
AI continues to contribute to real progress against the leading causes of disease and death. In healthcare today, deep learning supports faster, more accurate diagnosis, precision treatment planning, medical imaging, and analysis of large volumes of patient data. These tools are changing how care is delivered, and professionals across the sector now need a working knowledge of what AI can and cannot do.
This MOOC is a fast start for healthcare professionals, including those in non-technical roles, on the applications of AI. It focuses on deep learning and AI-based automation in clinical and organizational settings, covering practical topics such as medical imaging, model interpretability, AI mistrust, and the legal and ethical considerations of using AI in medicine. No prior experience with AI is required.
You choose how you participate:

The Practitioner Track is for clinicians, researchers, and administrators who want to demonstrate their learning through written clinical analysis, with no coding required.

The Builder Track is for those who want hands-on model implementation in Python and Kaggle, with step-by-step video guidance.

By the end, you will have the knowledge and confidence to engage in AI projects, advocate for responsible AI adoption, and identify opportunities to improve patient outcomes and operational efficiency.

This course gives you a solid understanding of AI's capabilities, benefits, and limitations, along with practical strategies to contribute to AI-driven innovation in your organization. You will learn how to:

Identify common tasks in a medical environment that can be solved with AI models

Describe how AI models are developed and trained to automate clinical tasks, and build one yourself if you take the Builder Track

Interpret the inner workings of AI models, the foundation of "understandable AI"

Mitigate challenges in the clinical use of AI, including AI mistrust and legal and ethical considerations

Evaluate and discuss the role of AI in real medical and organizational settings

The Applications of AI in Healthcare MOOC helps clinicians and other healthcare professionals, technical and non-technical, engage confidently with AI in clinical and organizational settings. You will explore deep learning, medical imaging, and AI ethics, and build the knowledge to advocate for responsible AI in your practice. Choose a no-coding Practitioner Track or a hands-on Builder Track , and earn the same HBKU-verified certificate.

Duration: 9 weeks

Skills:
- Advocacy
- Artificial Intelligence
- Automation
- Clinical Analysis
- Clinical Trials
- Data Analysis
- Deep Learning
- Ethical AI
- Ethical Standards And Conduct
- Health Administration
- Machine Learning
- Medical Imaging
- Medical Records
- Python (Programming Language)
- Research
- Responsible AI
- Treatment Planning

Curriculum:
- Identify common tasks in a medical environment that can be solved with AI models
- Describe how AI models are developed and trained to automate clinical tasks, and build one yourself if you take the Builder Track
- Interpret the inner workings of AI models, the foundation of "understandable AI"
- Mitigate challenges in the clinical use of AI, including AI mistrust and legal and ethical considerations

- Evaluate and discuss the role of AI in real medical and organizational settings