Christopher Newport University

What you'll study

The curriculum builds a strong foundation in computer science and mathematics before moving into specialised AI topics. Early years focus on programming, data structures and algorithms, discrete mathematics, linear algebra, probability and statistics, and systems courses. Later coursework emphasises machine learning, artificial intelligence principles, data mining, natural language processing, computer vision, and ethics in AI. Practical, project‑based learning is central: students work on team projects, data‑driven assignments, and a senior capstone that applies AI techniques to applied problems.

• Core topics: programming, data structures and algorithms, software engineering, operating systems, databases.
• Mathematical foundations: calculus, linear algebra, probability & statistics, discrete math.
• AI and ML courses: introductory AI, supervised and unsupervised learning, neural networks and deep learning, reinforcement learning, model evaluation and deployment.
• Applied areas: natural language processing, computer vision, robotics, data visualization and analytics.
• Professional and ethical skills: AI ethics, data privacy, communication, teamwork and project management.
• Experiential components: laboratory work, research with faculty, internships, and a capstone project integrating theory and systems development.

Entry requirements

Admission to Christopher Newport University typically looks for a strong academic record in secondary education with emphasis on mathematics and science. Prospective students are expected to demonstrate achievement in courses such as precalculus/calculus and physics where available, and to have experience with programming is advantageous but not always mandatory. The university considers the full application, including transcripts, personal statement, and recommendations; standardised tests may be optional depending on the applicant's circumstances. Transfer applicants should present college coursework in computer science and mathematics for advanced standing.

Career prospects

Graduates with an undergraduate degree focused on artificial intelligence pursue a wide range of technical and analytical roles. Common career paths include machine learning engineer, data scientist/analyst, software engineer with AI specialisation, computer vision or NLP developer, robotics engineer, and AI product or project roles. Alumni also move into research assistant positions, graduate study (master's or PhD) in AI, data science or related fields, or applied roles in industries such as healthcare, finance, defence, manufacturing, government, and technology startups. The programme’s emphasis on hands‑on projects and internships helps students build practical portfolios attractive to employers.

Why study at Christopher Newport University

Christopher Newport University offers a liberal‑arts environment with small class sizes and accessible faculty, enabling close mentorship and collaborative research opportunities for undergraduates. The university emphasises experiential learning: students have access to computing labs, interdisciplinary partnerships, and local internship networks in the Hampton Roads region. A personalised curriculum and senior capstone give students a chance to develop a demonstrable body of work in AI. For students seeking a balance of technical depth and broad communicative and ethical training, CNU provides a supportive setting to launch careers or graduate study in artificial intelligence and data science.