Current MD/MSAI Students

Electives Offered

MD/MSAI Students Only

• INTD 4111: Fast Healthcare Interoperability Resources (FHIR) for Medical Students
  • Offered during Block 1
  • FHIR for Medical Students delves into Fast Healthcare Interoperability  resources (FHIR). This course is tailored for medical student with experience in C#, Java, and/or JavaScript and those aiming to develop their skills with SMART on FHIR and CDS Hooks. The curriculum is hands-on with exercises, enabling participants to learn by both developing and reviewing practical software applications.
• INTD 4011: Capstone I
  • Longitudinal elective
  • The primary learning objective of this elective is to prepare students for the advanced use of machine learning (ML) and artificial intelligence (AI) techniques in the professional health field. Successful completion of this course will provide students with knowledge of applications of ML and AI to health and medicine with quarter long project approved by the instructor and mentor.
• INTD 4012: Capstone II
  • Offered during Block 8
  • This course is a continuation of Capstone I and applies an original/novel research idea in the data science domain.  The course aims to give students the skills to conduct original research with a mentor, write up their findings in preparation for publication to a journal, and ultimately submit them for publication.
• INTD 4300: Advanced Generative AI
  • Offered during Block 8
  • This 4-week elective provides a comprehensive introduction to Generative AI technologies with a specific focus on applications in medicine through structured morning lectures, interactive demonstrations, hands-on exercises, and assignments, students will explore fundamental concepts and practical applications of Large Language Models (LLMs). 

Open to all Long SOM Pre-Clinical Medical Students

• ELEC : Introduction to Generative AI
  • Still pending confirmation
  • Longitudinal elective
  • This longitudinal course provides a comprehensive introduction to Generative AI technologies with specific focus on applications in medicine. Through monthly 90-minute sessions combining lectures, interactive demonstrations, and hands-on exercises, students will explore the fundamental concepts and practical applications of Large Language Models (LLMs). 
  • To register for this class, contact gutierrezsr@uthscsa.edu for permission
• ELEC : Introduction to Python and Machine Learning
  • Still pending confirmation
  • Longitudinal elective
  • This year-long introductory enrichment course is to learn Python programming and explore its applications in Machine Learning. Participants will learn into Python basics, progressing to advanced topics like OOP and data manipulation. The course culminates with hands-on implementation of Machine Learning algorithms, including Random Forests and Neural Networks using NumPy. Each session features an in-class project to reinforce learning.
  • To register for this class, contact gutierrezsr@uthscsa.edu for permission

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