Program Overview

Data Science Master of Science Degree

Overview

Data science is one of the hottest fields in computing. The data science degree gives you the practical and theoretical skills to handle large-scale data management and analysis challenges that arise in today’s data-driven organizations. This program appeals to professionals looking to enhance their skill set, and includes opportunities for customized course work within the broad field of data science and its various application areas.

RIT’s Data Science Master’s: On-Campus or Online

In response to the growing need to generate and analyze meaningful data across all industries, demand is on the rise for a new breed of professionals skilled in both analytics and computing. RIT’s MS in data science encourages you to work with faculty experts in the fields of data science, analytics, and infrastructure who provide hands-on experience solving real problems. The curriculum includes opportunities for you to choose elective courses to pursue a variety of career paths within the broad field of data science and its various application areas. The program prepares you—regardless of your scientific, engineering, or business background—to pursue a career in data science.

What You'll Learn

• Concepts and skills in machine learning to prepare you to build, tune, and discover actionable insights from predictive models
• Programming language skills in Python and Java to be able to synthesize large unstructured data sets
• Competencies in data mining, regression analysis, text mining, and predictive analytics
• How to create, critically assess, interpret, and communicate rich visualizations

A Data Science Master’s Curriculum Packed with High-Demand Skills

The explosive growth in demand for data science skills is disrupting today’s job markets. These skills are found in over half of all job postings related to this field.

• Data Analytics: Data analysis skills are projected to grow in demand to 82% by 2026, and machine learning skills are growing by 1-2%.
• Data Science: Demand for skills in artificial intelligence is growing by 128% and deep learning skills demand is growing by 135%.
• Software and Programming: Demand for expertise in Python is growing by 21%; blockchain skills are growing by 245%.
• Experimental Design: Crossover, adaptive, and equivalence designs are dominating 38% of this job market.

Careers and Cooperative Education

Typical Job Titles

• Data Scientist
• Data Engineer
• Data Architect
• Machine Learning Engineer
• Data Analyst
• Database Administrator
• Statistician
• Business Analyst

Curriculum

Data Science, MS degree, typical course sequence (on-campus program)

• First Year
  • DSCI-601 | Applied Data Science I | 3
  • DSCI-633 | Foundations of Data Science and Analytics | 3
  • DSCI-644 | Software Engineering for Data Science | 3
  • ISTE-608 | Database Design And Implementation | 3
  • STAT-614 | Applied Statistics | 3
  • SWEN-601 | Software Construction | 3
  • Electives | 3
• Second Year
  • DSCI-602 | Applied Data Science II | 3
  • Electives | 6
• Total Semester Credit Hours | 30

Data Science, MS degree, typical course sequence (online program)

• First Year
  • DSCI-633 | Foundations of Data Science and Analytics | 3
  • ISTE-608 | Database And Implementation | 3
  • STAT-614 | Applied Statistics | 3
  • SWEN-601 | Software Construction | 3
  • Elective | 3
• Second Year
  • DSCI-644 | Software Engineering for Data Science | 3
  • DSCI-799 | Graduate Capstone | 3
  • Electives | 9
• Total Semester Credit Hours | 30

Data Science, MS degree, typical course sequence (online + edX program)

• First Year
  • ISTE-608 | Database Design And Implementation | 3
  • SWEN-601 | Software Construction | 3
  • edX Micromasters | 9
  • Elective | 3
• Second Year
  • DSCI-644 | Software Engineering for Data Science | 3
  • DSCI-799 | Graduate Capstone | 3
  • Electives | 6
• Total Semester Credit Hours | 30

Admissions and Financial Aid

Application Details

To be considered for admission to the Data Science MS program, candidates must fulfill the following requirements:

• Complete an online graduate application.
• Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
• Hold a baccalaureate degree (or US equivalent) from an accredited university or college. A minimum cumulative GPA of 3.0 (or equivalent) is recommended.
• Satisfy prerequisite requirements and/or complete bridge courses prior to starting program coursework.
• Submit a current resume or curriculum vitae.
• Submit a personal statement of educational objectives.
• Submit two letters of recommendation.
• Entrance exam requirements: GRE optional for Fall 2025 applicants. No minimum score requirement.

English Language Test Scores

International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver.

• TOEFL | 88
• IELTS | 6.5
• PTE Academic | 60

Cost and Financial Aid

An RIT graduate degree is an investment with lifelong returns. Graduate tuition varies by degree, the number of credits taken per semester, and delivery method.

Faculty

• Christian Newman | Associate Professor
• Michael Mior | Assistant Professor
• Zhe Yu | Assistant Professor

Resources

Current students in the on-campus data science master’s program may refer to these resources for additional information.

Related News

• January 15, 2025 | College of Computing to split Commencement into two ceremonies
• April 29, 2024 | Students discover research opportunities on the path to graduation
• April 3, 2023 | RIT Master Plan gives graduate tuition scholarship to eligible alumni

Contact

• Bethany Iraci-McBane | Admissions Counselor
• Travis Desell | On-Campus Program
• Erik Golen | Online Program