SYSEN 5650

SYSEN 5650

Course information provided by the 2025-2026 Catalog.

The course “Programming Essentials for Health AI and Data Science” is designed for advanced students and clinicians seeking to develop programming expertise in healthcare applications. This course provides hands-on experience with Python, Pytorch, data science/machine learning libraries, LLM and agents techniques, focusing on real-world health data, including EHRs, medical imaging, and clinical text. Participants will explore AI models for disease prediction, causal inference, and natural language processing etc. The course emphasizes practical implementation, from preprocessing messy health data to deploying AI models in clinical settings. Capstone projects will apply AI to real-world health challenges.


Enrollment Information REF-F25 Enrollment limited to: Systems Engineering Master of Engineering students, on-campus and distance learning.

Distribution Requirements (CE-EN)

Last 3 terms offered (None)

Learning Outcomes REF-FA25

  • Demonstrate the ability to preprocess, clean, analyze, and visualize real-world health datasets, including EHRs, medical imaging, and clinical text, using Python and data science libraries.
  • Identify and utilize appropriate Python/PyTorch development environments, tools, and libraries for implementing machine learning and deep learning techniques. These methods will be applied to health-related challenges such as disease prediction, computational phenotyping, effect estimation, classification, clustering, predictive modeling, and causal inference.
  • Demonstrate essential programming skills for advanced studies in fields like AI/ML in medicine, and NLP for healthcare, among others.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Graded

  • 20170 SYSEN 5650   LEC 001

    • TR
    • Aug 25 - Dec 8, 2025
    • Staff

  • Instruction Mode: Distance Learning-Synchronous

    Enrollment limited to: Systems Engineering on-campus students.

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Graded

  • 20171 SYSEN 5650   LEC 002

    • TR
    • Aug 25 - Dec 8, 2025
    • Staff

  • Instruction Mode: Distance Learning-Synchronous

    Enrollment limited to: Systems Engineering distance learning students.