140.618.49
AI Programming in Python for Public Health

Location
Internet
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2025 - 2026
Instruction Method
Synchronous Online
Class Time(s)
M, Tu, W, Th, F, 8:30am - 12:00pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Brian Caffo
Ahmed Hassoon
Contact Name
Brian Caffo
Frequency Schedule
Every Year
Prerequisite

Prior programming experience in python.

Description
This course is essential for anyone interested in leveraging the power of Artificial Intelligence to advance public health. It offers: Cutting-Edge Knowledge: Understand how AI technologies are revolutionizing public health, from epidemic forecasting to personalized healthcare. Practical Skills: Gain hands-on experience with AI tools and methodologies, making you a valuable asset in any health-related field. Broadened Perspectives: Explore the ethical, legal, and social implications of AI in healthcare, preparing you to make informed decisions in your professional practice. Future Preparedness: Equip yourself with the skills and knowledge to stay ahead in a rapidly evolving field, ensuri
Explores the transformative potential of Artificial Intelligence (AI) in public health. Aims at public health professionals, researchers, and policymakers, the course delves into AI’s role in disease surveillance, epidemic prediction, healthcare delivery, and health policy. Gains foundational knowledge in AI concepts, machine learning algorithms, and data analytics. Teaches how AI can address public health challenges, enhance disease prevention strategies, and improve health outcomes through case studies, interactive sessions, and hands-on projects. Emphasizes ethical considerations, data privacy, and the equitable application of AI technologies in diverse health settings.
Learning Objectives
Upon successfully completing this course, students will be able to:
  1. Explain key concepts and methodologies of Artificial Intelligence and their relevance to public health.
  2. Analyze and interpret AI-driven data to inform public health decisions and strategies.
  3. Apply AI tools and techniques to real-world public health challenges.
  4. Evaluate the ethical and legal implications of AI in healthcare.
  5. Contribute to the design and implementation of AI solutions in public health settings.
  6. Communicate effectively about the benefits and limitations of AI in public health to diverse audiences.
Methods of Assessment
This course is evaluated as follows:
  • 10% Participation
  • 30% Quizzes
  • 60% Project(s)
Enrollment Restriction
Students must know R or python.
Instructor Consent
Consent required for some students
Consent Note
Students must know R or python to be in this course.
Consent Contact
bcaffoweb@jhu.edu
Special Comments

This is the online/virtual section of a course also held onsite. You are responsible for the modality in which you register