Georgetown University’s “AI for Health Care Applications” Live Lecture and Office Hours series will return this spring, offering enrolled AIM-AHEAD Consortium members a structured opportunity to engage with the course content and connect with instructors throughout the learning process.

The series runs on alternating Mondays from March 2 through May 18, 2026, and includes six live lectures paired with six office hours sessions. Each session is one hour long and open to all learners enrolled in the course. Live lectures will begin on Monday, March 2, and conclude on May 11. Office hours will begin on March 9 and conclude on May 18.

These sessions accompany the AI for Health Care Applications course currently available on AIM-AHEAD Connect. Enrollment is available at no cost to AIM-AHEAD Consortium members, and participants may join at any time.

The course introduces core concepts in artificial intelligence and machine learning as applied to health care data. Materials are delivered through a series of self-contained notebooks written in Python and R, each paired with a recorded tutorial and example datasets. These notebooks guide participants through preparing data, building and evaluating models, and understanding how commonly used machine learning libraries function in practice. Interactive office hours via Zoom provide an opportunity for course participants to ask questions, review key concepts, and receive support from the course developers.

While there are no formal prerequisites, the content for this course is intended for learners who can write basic code in Python or R within a notebook environment but may not yet have experience with statistical learning or machine learning libraries. Participants will benefit from a foundational familiarity with coding and a willingness to work through hands-on examples. The material is developed at a master’s-level standard and is suitable for graduate students, motivated undergraduates, and professionals pursuing independent learning.

The notebooks are designed for use in Google Colab and require a Google account. They may be run in other Jupyter notebook environments; however, technical support is available only for Colab.

Course Objectives:

• Preparing and formatting data for model training and validation
• Training and evaluating predictive classification models
• Improving model performance through tuning and iteration
• Applying foundational machine learning methods to new datasets

Course Modules:

• Introduction to Classification
• Unsupervised Learning: K-Means Clustering
• Handling Non-Linearity, Model Complexity, and Regularization
• Model Selection, Hyperparameter Tuning, and Evaluation
• Introduction to Neural Networks
• Natural Language Processing

Spring 2026 Schedule

All sessions will be from 2:00 - 3:00 PM CT / 3:00 - 4:00 PM ET. Registration is required in order to receive the Zoom link. Course participants must be members of AIM-AHEAD Connect and may register separately for the Live Lecture and Office Hours sessions.

Consortium members enrolled in the course are encouraged to attend the live lectures and office hours to reinforce learning, ask questions, and engage with the course developers and peers. To enroll, sign in to AIM-AHEAD Connect, select Courses from the left-hand navigation menu, open the AIM-AHEAD Course Catalog, and choose AIM-AHEAD Introductory Course: AI for Health Care Applications before clicking Enroll.

Related Links:

• Georgetown University “AI for Health Care Applications” Live Lecture Registration: https://signup.aim-ahead.net/event/p/B8b27F660e
• Georgetown University “AI for Health Care Applications” Office Hours Registration: https://signup.aim-ahead.net/event/p/22B9272081
• AIM-AHEAD Connect Course: AI for Health Care Applications: https://courses.aim-ahead.net/course/c/AIMLConcepts
• Join AIM-AHEAD Connect: https://connect.aim-ahead.net/
• AIM-AHEAD Connect Course Catalog: https://courses.aim-ahead.net/course/catalog