Design and implement reliable software and data systems
Degree Program
Computer Science & Artificial Intelligence
Computer Science & Artificial IntelligenceDegree Program · Computing, Communication & Enterprise
Computational Intelligence & Data Systems
Combines computer science, AI, data engineering, research computing, visualization, systems thinking, and responsible application.
Program purpose
Bachelor of Science
Students build software and data foundations, develop intelligent systems, evaluate model performance, and apply computation to scientific, cultural, organizational, and public problems.
Learning outcomes
What graduates are prepared to do
Program outcomes connect disciplinary knowledge to methods, judgment, communication, and independently evaluated work.
Develop and evaluate machine-learning and AI applications
Build reproducible computational workflows and visualizations
Address privacy, security, bias, provenance, and human use
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
Programming, algorithms, mathematics, and statistics
- 02
Data structures, databases, software, and systems
- 03
Machine learning, AI, data science, and visualization
- 04
Responsible computing and applied electives
- 05
Computational systems capstone
Course sequence
Selected curriculum
CS-110
Computational Thinking & Programming
Introduces programming, algorithms, data, abstraction, testing, and computational problem solving through research and applied examples.
- Requirement
- Core
- Credits
- 3.0
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
Computational Systems Capstone
Guides a substantial software, data, AI, communication, publishing, or enterprise system from problem definition through delivery and evaluation.
- Requirement
- Core
- Credits
- 4.0
Learning environments
Field, laboratory & studio work
- Research computing laboratory
- AI and data systems studio
- Visualization and interaction environments
- Applied projects
Professional directions
Where the capability can lead
- Software and data engineering
- AI and machine-learning systems
- Research computing
- Analytics and visualization
- Graduate study in computing
Culminating work
Capstone, thesis, dissertation, or professional demonstration
A senior capstone delivers a working software, data, or AI system with evaluation, documentation, and a public or professional demonstration.
Admissions preparation
Materials and background
Admissions review considers preparation, purpose, prior work, and the fit between the applicant’s goals and the program.
Secondary-school completion or recognized equivalent
Academic records demonstrating preparation for college-level work
Statement connecting the applicant’s interests to the program
Writing or project sample when relevant to the pathway
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.