Artificial Intelligence in Medicine (CERT)

The admission standards for the Graduate Certificate program in Artificial Intelligence in Medicine are as follows:

  1. All admission applications for the Graduate Certificate program shall include:
    1. A completed graduate application for the Graduate School
    2. Application fee
    3. Official transcript certifying at least a bachelor's degree.  All transcripts not in English must be certified as authentic and translated verbatim into English.
  2. The minimum requirement for admission is the baccalaureate degree or its equivalent from an accredited institution, or current enrollment in a graduate Speed School program, and completion of an introductory computer programming course or previous exposure to programming. Students without this course are encouraged to apply but may be asked to take a pre-requisite course in computer programming. 
  3. The successful applicant will typically have an undergraduate grade point average of 3.0 or above (on a 4.0 scale).
  4. International students whose primary language is not English must show English language proficiency. Applicants must either submit an official TOEFL, IELTS or Duolingo score, or demonstrate a degree award from an acceptable English language institution.  The successful applicant will typically have a total TOEFL score of 79 or higher, an overall IELTS score of 6.5 or higher or Duolingo score of 105.

Students can enroll in a Graduate Certificate program either as a non-degree seeking student or as a student simultaneously enrolled in a graduate degree program and this graduate certificate program.  Students who wish to earn a graduate degree must meet all admission criteria for the degree program.

All students enrolled in a graduate certificate program are expected to make steady and satisfactory progress toward the completion of the certificate. Students who are not enrolled for a period of more than 12 months will be considered to have withdrawn from the certificate program. Students who seek to return after such a period of time must contact the graduate program director.

The following certificate requirements are mandatory of all Graduate Certificate candidates:

  1. The Certificate Program of Study must be completed with a 3.0 GPA or better for all graduate courses used to satisfy certificate requirements.
  2. Graduate certificate students must take all certificate course work at the University of Louisville. No transfer credits will be accepted towards a graduate certificate.

The Bioengineering Department has established the following grade policy for the Artificial Intelligence in Medicine Graduate Certificate program:

  1. A student cannot receive a C+ or lower grade in courses counting towards the certificate. 

Additionally, all program requirements for this certificate must be completed within three years from admission into the program.

Program Requirements

Choose 12 credit hours from the list below (9 credit hours must be from BE courses):12
LabVIEW for Bioengineers
Machine Learning in Python
Machine Learning in Medicine
Medical Image Computing
Computer Tools for Medical Image Analysis
Artificial Intelligence Techniques in Digital Pathology
Introduction to Artificial Intelligence in Bioengineering
Computational Methods for Medical Image Analysis
Artificial Intelligence and Radiomics
Modeling of Biological Phenomena
Python and Data Analytics
Artificial Intelligence
Introduction to Machine Learning
Deep Learning Algorithms and Methods
Special Topics in Computer Science and Engineering (Big Data Analytics Tools & Tech)
Data Mining
NOTE: Only one of either CSE 632 or PHMS 641 can count towards certificate
Medical Imaging Systems
Introduction to Bioinformatics
Special Topics in Computer Science and Engineering 1
Introduction to Statistical Computing
Basic Statistical Methods for Bioinformatics
Biostatistical Methods II
Advanced Statistical Computing I
Data Mining I
Data Mining II
Minimum Total Hours12

CSE 694 Special Topics options:

  1. Current topics in Bioinformatics
  2. Topics in Advanced Machine Learning Theory & Methods