Courses / Generative AI in Biomedicine
Module 6 of 7
Generative AI in Biomedicine
Discover how generative AI and large language models are reshaping biomedical research. This module introduces GANs, VAEs, transformer architectures, and advanced LLM applications. Learners practice prompt engineering, biomedical text summarization, and research acceleration techniques such as automated literature synthesis and hypothesis generation.
Free
Format · Online
Start date · Aug 31, 2026
Duration · 2 weeks
Time · 5 hrs / week
Microskills · 7
CME credits · 11
What you will gain
Course Outcomes
Integration of AI techniques
Integrate AI and ML into healthcare research and clinical practice.
Real-world data application
Use real medical data and case studies to address healthcare challenges.
Practical AI skills
Work with code-free AI/ML tools — no programming knowledge needed.
Critical thinking
Analyze complex healthcare problems through AI-driven insights and methodologies.
What you will learn
Microskills in this Module
Each module covers 5 AI microskills plus one Scientific Rigor and Reproducibility (SRR) and one Responsible Conduct of Research (RCR) microskill.
- Fundamentals of generative biomedical AI
- Fundamentals of large language models
- Large language models (LLMs) in biomedicine
- Prompt engineering for biomedical applications
- Utilizing LLMs for accelerating biomedical research
- Evaluation and reproducibility of AI-generated data
- Ethical dissemination of generated biomedical content
Meet your instructors
Expert Faculty from the University of Florida
Azra Bihorac MD, MS
Senior Associate Dean for Research Affairs · Director, IC3
Ashish Aggarwal MS
Instructional Associate Professor
Benjamin Shickel PhD
Asst. Professor · Associate Director, IC3
Zhenhong Hu, PhD
Research Assistant Professor
Jeremy Balch MD
General Surgery Resident
Akshith Ullal, PhD
Data Scientist
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Ready to enroll?
Free enrollment. No coding required. Two cohorts per year — Spring and Fall.