Master's Admissions

Admission Requirements

General guidelines for applying to a graduate program at the University of Pittsburgh should be reviewed prior to submitting an application for admission. These guidelines are available on the University’s Application for Admission Catalog page.

The School of Computing and Information seeks students with diverse interests and abilities for its graduate degree and certification programs. All applicants will be judged on their own merits. Applicants for master’s study must have earned a bachelor’s degree from an accredited college or university with a scholastic average of B (3.0 on a 4.0 scale) or better; the doctoral programs have more stringent requirements. For those who have been in the workforce, admission will be based upon academic achievement, area of study, career orientation and work experience.

Apply Online: Applications for graduate study must be completed and submitted entirely online. Applicants must set up a free account that enables you to work on your application over several sessions. Your information is transmitted through a secured server and is kept private until you submit your application. After submission, your application materials will be managed confidentially within the review process.

Individual programs require supplemental application materials, and some programs require prerequisite coursework and skills knowledge. More details regarding expectations for the statement of intent or writing portfolio, pre-requisite courses, and other supplemental application materials can be found below.

Deadlines

Application deadlines can be found on our graduate FAQ page.

Program Specific Requirements

Master of Data Science

To gain admission to the MDS program, you’ll complete a 3-credit pathway course on the Coursera platform. By earning a GPA of 3.0 or higher on a 4.0 scale in that course, you’ll be accepted into the degree program upon bachelor’s degree verification.

Learn more about the program’s admissions process here.

Master of Library and Information Science

The Department of Information Culture and Data Stewardship (ICDS) seeks students with diverse educational and career backgrounds. By nature, MLIS degrees are multi-disciplinary, and the faculty welcomes applicants with bachelor’s degrees and/or advanced degrees from diverse disciplinary backgrounds.

The MLIS degree does not require specific coursework for admission nor the Graduate Record Exam (GRE).

When applying ot the MLIS program, applicants indicate their preference for either the online or the on-campus program.

The MLIS Admissions Committee makes all decisions on MLIS applicants.

Master of Science in Computer Science

The department is open to applications from exceptional students transitioning to graduate study in Computer Science from other undergraduate fields. Transitional students with demonstrated computing aptitude, as evidenced by outstanding grades in at least 4 of the required computer science courses noted below, may be considered for admission to the graduate program. Completed minimally a selection of courses in the following topical areas (the corresponding Pitt course numbers are indicated):

In Computer Science, one course in each of:

In Mathematics, the following:

At the time of enrollment, the student must hold a BS degree.

Master of Science in Information Science

Applicants for graduate study must have earned a baccalaureate degree from an accredited college or university with a scholastic average of B (3.0 on a 4.0 scale) or better.

Prerequisites for admission to the Master of Science in Information Science (MSIS) degree program include one (three-credit or higher) college course in each of the following (the corresponding Pitt course numbers are indicated):

  • Programming: A course on object-oriented programming using Java, Python, C#, or C++. (CMPINF 0401)
  • Probability and Statistics: A course covering data collection, descriptive and inferential statistics is optimal. It should cover measures of central tendency and variability, regression, correlation, non-parametric analysis, probability, and sampling, Bayesian analysis, significance tests, and hypothesis testing. (STAT 0200 or STAT 1000)
  • Mathematics: A college-level mathematics course in linear algebra, calculus, or discrete mathematics (MATH 0120MATH 0220, or MATH 0400)

Master of Science in Telecommunications

Applicants for graduate study must have earned a baccalaureate degree from an accredited college or university with a scholastic average of B (3.0 on a 4.0 scale) or better.

Prerequisites for admission to the MST degree program include one college course (3 credits or more) in each of the following (the corresponding Pitt course numbers are indicated):

  • Programming: A course on object-oriented programming using Java, C#, or C++. (CMPINF 0401)
  • Probability and Statistics: A course covering data collection, descriptive and inferential statistics is optimal. It should cover measures of central tendency and variability, regression, correlation, non-parametric analysis, probability, and sampling, Bayesian analysis, significance tests, and hypothesis testing. (STAT 0200 or STAT 1000)
  • Mathematics: A college-level mathematics course, in linear algebra, calculus, or discrete mathematics (MATH 0120, MATH 0220, or MATH 0400)