Design advanced research-computing and AI workflows
Degree Program
Data Science & Research Computing
Data Science & Research ComputingDegree Program · Computing, Communication & Enterprise
Applied AI, Research Computing & Visualization
Advanced computational methods for research, data-intensive inquiry, AI systems, visualization, reproducibility, and decision environments.
Program purpose
Master of Science
Students develop transparent and evaluable computational workflows that combine data engineering, machine learning, AI, simulation, visualization, and domain evidence.
Learning outcomes
What graduates are prepared to do
Program outcomes connect disciplinary knowledge to methods, judgment, communication, and independently evaluated work.
Develop rigorous evaluation and reproducibility practices
Create visual and interactive representations of complex evidence
Deliver a thesis, method, or technical system grounded in domain needs
Curriculum architecture
How the pathway is organized
Coursework progresses from foundations to methods, integration, and a culminating demonstration of capability.
Foundations
Build the knowledge, skills, and mindset for inquiry.
Application
Apply methods and tools to real-world questions.
Integration
Synthesize across disciplines and perspectives.
Demonstration
Produce and present work that creates impact.
- 01
Advanced programming and data systems
- 02
Machine learning, AI systems, and evaluation
- 03
Research computing, visualization, simulation, and reproducibility
- 04
Domain application and responsible computing
- 05
Thesis or technical project
Course sequence
Selected curriculum
AI-210
Machine Learning Foundations
Introduces supervised and unsupervised learning, model evaluation, features, data quality, bias, and responsible application.
- Requirement
- Core
- Credits
- 3.0
Applied AI Systems
Builds AI-enabled applications using models, retrieval, tools, evaluation, guardrails, and human review within a documented system architecture.
- Requirement
- Core
- Credits
- 3.0
Data Management & Reproducible Research
Develops durable data structures, metadata, versioning, cleaning, provenance, documentation, and reproducible analysis workflows.
- Requirement
- Core
- Credits
- 3.0
Research Computing & Visualization
Uses computational notebooks, scripting, visualization, statistical workflows, and research software practices to analyze and communicate complex evidence.
- Requirement
- Core
- Credits
- 3.0
Complex Adaptive Systems
Examines emergence, feedback, adaptation, networks, path dependence, scale, and agent interaction across social, biological, environmental, and technological systems.
- Requirement
- Core
- Credits
- 3.0
Methodological Notes Studio
Produces concise, transparent methodological publications that document workflows, adaptations, validation, failures, and reusable research practice.
- Requirement
- Core
- Credits
- 3.0
Learning environments
Field, laboratory & studio work
- Research computing environment
- AI and data systems studio
- Visualization and interactive media
- Cross-division research laboratories
Professional directions
Where the capability can lead
- Applied AI and data science
- Research software engineering
- Scientific visualization
- Computational research leadership
- Doctoral study
Culminating work
Capstone, thesis, dissertation, or professional demonstration
A thesis or technical project delivers a validated AI, data, visualization, or research-computing system and a reproducible documentation package.
Admissions preparation
Materials and background
Admissions review considers preparation, purpose, prior work, and the fit between the applicant’s goals and the program.
Bachelor’s degree or recognized equivalent
Academic records and evidence of disciplinary or methodological preparation
Statement of purpose identifying questions, methods, and intended outcomes
Writing, research, technical, or professional sample
Two academic or professional recommendations
Faculty & academic leadership
Program relationships
Next step
Connect this pathway to your academic goals.
Request information for a focused conversation or begin an application through the Stella Nova Student Information System.