BMI 6335 Technical Foundations of Generative Artificial Intelligence

3 semester credit hours
Lecture contact hours: 2; Lab contact hours: 3
Web-based and classroom instruction
Prerequisite: BMI 5007

Generative Artificial Intelligence (AI) holds immense potential to revolutionize the field of biomedicine by enhancing accuracy, efficiency, and personalization in healthcare, ultimately leading to better patient outcomes and a more robust healthcare system. It is crucial in improving diagnostic capabilities, personalized medicine, drug discovery, clinical decision support, and patient engagement and support.

This course provides fundamental and technical skills in generative AI, offering hands-on experience with Large Language Models (LLMs), Stable Diffusion Models, and Generative Adversarial Networks (GANs). Students will engage in using generative AI to solve real-world biomedical problems and will be critically evaluated on their methodology and results.

Upon successfully completing this course, students will:

• Select an appropriate generative AI model for a specific data science task.
• Modify, adapt, and deploy generative AI models for specific biomedical problems.
• Train, evaluate, and compare the outputs of generative AI.
• Identify the ethical and real-world implementation implications of generative AI models.

Last Update: 06/20/2024