Programs

Information about faculty and research can be found on the Goergen Institute for Data Science and Artificial Intelligence website.

AdmissionsLink to section

Applying to Advanced CertificatesLink to section

To be considered for admission into the Data Science Advanced Certificate and the Advanced Certificate in Healthcare Data Science and AI, a student must have completed a bachelor’s degree. All majors are considered. They should have one year or the equivalent of coursework in undergraduate calculus and linear algebra, proficiency in introductory programming and data structures (Python or Java) through coursework or equivalent experience, and interest in and motivation to pursue large-scale quantitative data analytics.

Applying to Master's ProgramsLink to section

The Master of Science in Data Science program is seeking motivated, qualified, and well-rounded applicants. A bachelor’s degree is required, preferably in a STEM field (but not required). Prospective students should have undergraduate mathematics experience through basic calculus, but do not need college-level statistics or data analytics. For admission to the MS Data Science program, applicants also should have some programming experience. For admission to the MS Healthcare Data Science and AI program, preferred prospective students should demonstrate experience or interest in healthcare. Admission to the program is decided by the graduate admissions committee.

Materials required for application:

• Graduate program online application
• Academic transcripts
• Statement of purpose
• Resume or curriculum vitae (CV)
• Three letters of recommendation (two for Healthcare Data Science and AI)
• For non-native English speakers: Official English-language proficiency test scores are required. TOEFL, IELTS, and Duolingo scores are acceptable.
• GRE scores (optional)

Applying to Advanced CertificatesLink to section

To be considered for admission into the Data Science Advanced certificate, a student must have completed a bachelor’s degree. All majors are considered. They should have one year or the equivalent of coursework in undergraduate calculus and linear algebra, proficiency in introductory programming and data structures (Python or Java) through coursework or equivalent experience, and interest in and motivation to pursue large-scale quantitative data analytics.

Materials required for application:

• Online application
• Official transcript(s) from bachelor’s degree (plus any other higher education experiences)
• Personal statement
• Resume/CV
• Two letters of recommendation (must be received by application deadline)
• Optional GRE and TOEFL/IELTS scores

AcademicsLink to section

Advanced Certificates and RequirementsLink to section

The Advanced Certificate in Data Science program is 16 credits, or the equivalent of four graduate-level courses. The program can be completed in two to four semesters of part-time study. There are three different course plans designed to suit each student’s unique background and level of preparation. Students interested in transferring credits earned from the advanced certificate to the master of science (MS) in data science program should contact the program coordinator.

The Advanced Certificate in Healthcare Data Science and AI is a 16-credit certificate program that covers applied and theoretical aspects of artificial intelligence pertaining to healthcare and is designed to be completed in two semesters of part-time study (two courses per semester) or four semesters of part-time study (one course per semester).

Required courses (12 credits):

• DSCC 485: Introduction to Privacy, Fairness and Ethical Considerations for Healthcare Data Science
• DSCC 486: Applied Machine Learning and Healthcare Data Mining
• DSCC 488: Deep Learning and Generative AI for Healthcare

Select one of the following (4 credits):

• DSCC 481: Python Programming and Tools for Data Science
• DSCC 482: Statistical Foundations and Data Visualization
• DSCC 484: Healthcare Data Management and Clinical Informatics
• DSCC 487: Inferential Statistics for Data Science

Master's Degrees and RequirementsLink to section

The Goergen Institute for Data Science offers a program of study leading to a Master of Science degree. The 30-credit interdisciplinary degree program is completed in two to three semesters of full-time study. Students can select a concentration in computational and statistical methods, health and biomedical science, or business and social science by completing eight credits of elective courses in one area in addition to the required core courses. All students participate in an industry practicum course, serving as their Plan B (non-thesis) exit exam.

In 2023, a new track in Genomics was approved by the New York State Department of Education which totals 33 credits and covers theoretical and applied aspects of data science and genomics. A Genomic Intensive Data Science Research, Education and Mentorship (GIDS-REM) fellowship is available to applicants interested in the genomics track.

The components of the program are:

• An optional summer bridging course for students who come without a strong computer science background
• Four required core courses
• A required four-credit practicum: Students work in teams to implement a significant system or analysis. Each student gives a final oral presentation.
• A minimum of three electives selected from the area courses or research, for a total of 10 credits or more.

In 2025, the Goergen Institute for Data Science began offering a program of study leading to a Master of Science degree in Healthcare Data Science and Artificial Intelligence The 32-credit interdisciplinary degree program covers applied and theoretical aspects of data science and artificial intelligence pertaining to healthcare and is designed to be completed in 4-8 semesters of part-time study or two semesters of full-time study. All students participate in an healthcare practicum course, serving as their Plan B (non-thesis) exit exam.

The components of the program are:

• Eight required courses which includes the practicum.
• A required four-credit practicum: Students work in teams to implement a significant system or analysis. Each student gives a final oral presentation.

Advanced Certificates and RequirementsLink to section

The Advanced Certificate in Data Science program is 16 credits, or the equivalent of four graduate-level courses. The program can be completed in two to four semesters of part-time study.

There are three different course plans designed to suit each student’s unique background and level of preparation.

Students interested in transferring credits earned from the advanced certificate to the Master of Science (MS) in data science program should contact the program coordinator.

Graduate Course TitlesLink to section

• DSCC 401: Tools for Data Science
• DSCC 402: Data Science at Scale
• DSCC 410: Digital Imaging
• DSCC 420: Introduction to Random Processes
• DSCC 435: Optimization for Machine Learning
• DSCC 440: Data Mining
• DSCC 442: Network Science Analytics
• DSCC 449: Computer Models of Perception and Cognition
• DSCC 461: Database Systems
• DSCC 462: Computational Introduction to Statistics
• DSCC 463: Data Management Systems
• DSCC 465: Introduction to Statistical Machine Learning
• DSCC 475: Time Series Analysis and Forecasting in Data Science
• DSCC 481: Python Programming and Tools for Data Science
• DSCC 482: Statistical Foundations and Data Visualization
• DSCC 483: Data Science Practicum
• DSCC 484: Healthcare Data Management and Clinical Informatics
• DSCC 485: Introduction to Privacy Fairness and Ethical Considerations for Healthcare Data Science
• DSCC 486: Applied Machine Learning and Healthcare Data Mining
• DSCC 487: Inferential Statistics for Data Science
• DSCC 488: Deep Learning for Healthcare
• DSCC 489: Healthcare Data Science Practicum
• DSCC 491: Master’s Research
• DSCC 494: Internship
• DSCC 495: Master’s Independent Study
• DSCC 511: Large Language Models
• DSCC 897: Master’s Dissertation