Foundations of Large Language Models in Medical Research
Self-Paced Online
1/7/2026 - 1/6/2027
$150
4 Hours
Discover how large language models are reshaping biomedical research. This course introduces the essential concepts, ethics, and practical skills necessary to safely and effectively use generative AI in healthcare and research settings.
Summary
This introductory course lays the foundation for understanding how generative Artificial Intelligence (AI) and large language models (LLMs) are transforming biomedical research. Participants explore the opportunities and risks of integrating AI into research workflows, including issues of bias, safety, HIPAA compliance, and institutional governance. Through guided activities in prompt engineering and tool demonstrations, learners acquire practical skills to safely and effectively use LLMs in medical research contexts.
Learning Objectives
At the end of this course, learners will be able to:
- Explain the role of generative AI and LLMs in addressing key challenges in biomedical research.
- Identifying and applying safe, compliant, and ethical practices for using LLMs under HIPAA and institutional guidelines.
- Construct effective prompts using foundational prompt engineering techniques for biomedical research tasks.
- Explore and evaluate LLM tools and platforms for compliant use in research environments.
Access to this online course is available from the date of purchase until it expires on January 6, 2027.
The Foundations of Large Language Models in Medical Research course is an online self-paced course that can be completed in approximately four hours. The course is delivered in five modules:
- Why Generative AI? Why now?
- Bias, Safety, Regulation and Governance
- HIPAA and Institutional LLM Guidelines
- Prompt Engineering Essentials
- Using OpenEvidence and OpenAI Models
To complete this program, you must review modules 1-5, achieve a score of 80% or higher on the summative exam, and complete all required surveys. You will be awarded a certificate that you can download or print upon fulfilling these requirements.
Technical Requirements
- Computer with internet access
- Speaker or headset
- Full sized monitor
- Web browser
This course is suitable for learners at any level of interest in using large language models in medical research. Clinicians, coordinators, data analysts, and researchers will all benefit from the course material.
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Jaleh Zand, Ph.D.Director of Artificial Intelligence, Division of Nephrology and HypertensionDr. Zand earned her PhD in Artificial Intelligence from the University of Oxford. With more than 15 years of experience in machine learning, data modeling, and analysis, she has leveraged her skills to address real-world problems in both academia and industry. |
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Shauna Overgaard, Ph.D.Senior Director, AI Strategy and FrameworksCo-Director, AI Validation and Stewardship ProgramShauna Overgaard, PhD, is Senior Director of AI Strategy and Frameworks at Mayo Clinic and Co-Director of its AI Validation and Stewardship Program. She designs risk-tiered assurance frameworks for LLM-enabled research, translating prototypes into reliable, decision-grade tools. Her work integrates human factors, statistical and clinical validation, and lifecycle monitoring, linking claims to auditable, provenance-rich evidence with clear limits-of-use and equity safeguards. Nationally, she co-chairs the National Academy of Medicine AI Code of Conduct (Health Systems and Payers). She serves on the editorial board of npj Health Systems and is a guest editor for BMJ Health and Care Informatics and Mayo Clinic Proceedings: Digital Health. She was recognized as a Rising Star in Modern Healthcare’s 2025 Leading Women in Healthcare. |
This course is available free of charge to Mayo Clinic employees thanks to support from the Mayo Clinic Center for Clinical and Translational Science (CCaTS).
Mayo Clinic employees - To enroll, click Login along the top navigation and click on the Mayo Clinic Employee Log In button. The course cost will display as free of charge at the bottom of the page and when the course has been added to the shopping cart.
Frequently Asked Questions
Who is the intended audience for this course?
This course is suitable for learners at any level of interest in using large language models in medical research. Clinicians, coordinators, data analysts, and researchers will all benefit from the course material.
Is the course geared toward participants internal to Mayo?
The content of this course is geared toward participants both internal and external to Mayo Clinic.
Is a certificate issued upon completion of the course? If so, what kind?
Attendees will receive a certificate of participation.
Is there a discount for Mayo Clinic employees?
Yes, we are pleased to offer this course free of charge to Mayo Clinic employees thanks to support from the Mayo Clinic Center for Clinical and Translational Science (CCaTS). To enroll, click Login along the top navigation and click on the Mayo Clinic Employee Log In button. The course cost will display as free of charge at the bottom of the page and when the course has been added to the shopping cart.
