Intelligent Systems, MS

The Intelligent Systems Program is a multidisciplinary graduate program at the University of Pittsburgh dedicated to applied artificial intelligence (AI). Many of Pitt’s acclaimed schools are represented through our associated faculty, including the School of Medicine, the School of Law, the School of Education, the Swanson School of Engineering, and the Kenneth P. Dietrich School of Arts and Sciences.

What Do We Offer?

  • Broadly interdisciplinary approach: We offer a strong, well-balanced foundation in the fundamentals of AI and many opportunities for advanced research and training in many disciplines, including computer science, biomedical informatics, cognitive psychology, information science, education, law, and more.
  • Focused, customized curricula: Building on the core curriculum, you will design your own personalized curricula that will prepare you for interdisciplinary research in your areas of interest.
  • Collaborative atmosphere: Faculty members and students present their research in regular program seminars, which exposes you to a broad range of research topics and methods, affording you the opportunity to present your own research.
  • Highly motivated faculty: Pitt’s widely published ISP faculty are leaders in their fields. Drawing on the strengths of diverse sectors of the university, and participating in over 30 funded research projects, they support graduate students through collaborative research, personal mentoring, and external research funding.

Degree Requirements

Students pursuing the Master of Science degree in ISP must adhere to the SCI requirements for graduation and complete a minimum of 30 credits as outlined below, as well as an MS Project. Students must also earn a grade of B- or better in each of the courses in the appropriate ISP curriculum (the general track or the Biomedical Informatics track) and maintain a QPA of at least 3.0.

General Track Curriculum

First-year students are encouraged but not required to take:

Core

AND choose two of the following:

Theory

Applied or mathematical statistics. Choose one of the following:

  • BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS 1
  • BIOST 2042  - INTRODUCTION TO STATISTICAL METHODS 2
  • BIOINF 2118  - STATISTICAL FOUNDATIONS OF BIOMEDICAL INFORMATICS
  • STAT 2131  - APPLIED STATISTICAL METHODS 1
  • STAT 2132  - APPLIED STATISTICAL METHODS 2

Theory of computation, algorithms. Choose one of the following:

One additional course required. Any of the theory courses listed above are acceptable.

Advanced courses

Four ISSP advanced lecture courses, numbered 2000 or higher and approved by the academic advisor.

Biomedical Informatics Track (ISP/MI)

This assumes that a student already has training in a health care field. If this is not so, then the faculty will select a set of courses that teach the student basic medical knowledge, and the student may take these courses as electives.

First-year students are encouraged but not required to take:

Core

Then choose one of the following:

AND choose one of the following:

AND choose one of the following:

  • BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS 1
  • BIOST 2042 - INTRODUCTION TO STATISTICAL METHODS 2
  • BIOINF 2118 - STATISTICAL FOUNDATIONS OF BIOMEDICAL INFORMATICS
  • STAT 2131 - APPLIED STATISTICAL METHODS 1
  • STAT 2132 - APPLIED STATISTICAL METHODS 2

AND choose two of the following:

Three (3) Graduate level (2000 or higher, three (3) credits) ISSP lecture courses that have been approved by your advisor as being relevant to your studies in the ISP.

For more degree requirement details, visit the Intelligent Systems, MS course catalog.

Admissions Requirements