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University of Pittsburgh    
2026-2027 Graduate & Professional Studies Catalog 
    
 
  Jul 18, 2026
 
2026-2027 Graduate & Professional Studies Catalog

Master of Data Science


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This online professional master’s degree builds upon strengths that span the School’s three departments, providing broad perspectives on topics related to the collection, management, processing, and stewardship of data; data-driven problem-solving and information ethics; and the selection, application, and evaluation of various approaches to predictive modeling and machine learning. This curriculum emphasizes workforce readiness, with a focus on real-world, data-oriented problem solving and portfolio-building projects throughout. To reach a broad audience, this program is offered via an online, flexible, well-structured, asynchronous modality to increase access to and completion of the degree by working professionals. Additionally, this degree builds upon the School’s Applied Data-Driven Methods Graduate Certificate , which has no STEM prerequisites for admission nor assumption of programming experience to target a diverse population of adult learners from many disciplinary backgrounds.

Admissions Requirements


Admission to this program requires completion of a bachelor’s degree from a regionally accredited institution in the United States or the completion of education that the University of Pittsburgh deems equivalent to a U.S.-accredited 4-year bachelor’s degree.
 
To be admitted to the program, eligible students must:

  • Complete a brief web-based enrollment form
  • Earn a grade of B or better in CMPINF 2100: Data-Centric Computing (Performance-Based Admissions Course)
  • Verification of completion of a bachelor’s degree from an accredited university of college

Upon completion of the above, students will be admitted to the Master of Data Science program.  Note that International students must demonstrate English language proficiency as required by University of Pittsburgh policy. Applicants who have completed the equivalent of a bachelor’s degree at an institution outside of the United States are required to provide an official third-party (NACES members) document-by-document assessmentof equivalency to a U.S.-accredited 4-year bachelor’s degree.
 
For further information about beginning our Performance-Based Admissions processes, please see the program web page.

Academic Regulations and Standards


The Master of Data Science is goverened by the University’s policies at large including full-time/part-time status, adding and dropping courses, repeating courses, grading systems,etc. Students should refer to the University’s Academic Regulations for general information.  For information specific to the School of Computing and Information, please refer to the SCI Graduate page .

Academic Standing and Dismissal

Academic standing is maintained and monitored each term by the Dean’s Office. To be in good academic standing, students are expected to maintain a cumulative GPA of 3.00 or above and make continued progress toward their degree. Students are placed in the Academic Notice status after earning a cumulative GPA below 3.00. Students return in Good Academic status after earning a cumulative GPA of 3.00 or above and making continued progress toward their degree.

Students placed on Academic Notice will be notified in writing via their Pitt email by the Dean’s Office.  Students who are on Academic Notice for failing to meet GPA requirements must earn a GPA of at least 3.00 for each term that they enroll until they have achieved a cumulative GPA of 3.00 or above.  If such a student fails to earn at least a 3.00 term GPA in two consecutive terms they are subject to Academic Dismissal.

Degree Requirements


This is an online professional master’s degree requiring 30 credits of coursework completed. The minimum passing grade in a course is C. The minimum cumulative GPA required for graduation is 3.0. General policies governing this professional master’s degree can be found on the School of Computing and Information 

The distribution of credits is outlined below.

Electives


Students must complete three (3) electives. The list below includes electives currently offered for the MDS program. More electives will be developed as the program grows.  All electives require one or more foundational courses as pre-requisites.

Capstone


The Master of Data Science culminates in a required capstone.  Students will apply their data science knowledge to real-world scenarios and will engage with provided datasets accompanied by detailed contextual information that simulates authentic business environments and organizational objectives.  This capstone experience requires students to synthesize knowledge from their previous coursework while exercising independent problem-solving and critical-thinking skills.  The course emphasizes the practical application of data science within relevant social, organizational, and instructional contexts.

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