Full Sail University

Programme overview

This concentration is offered as a specialized track within a Bachelor of Science degree, combining core undergraduate computing or technical coursework with focused classes on artificial intelligence concepts and applications. The curriculum balances theoretical foundations, practical implementation, and professional skills so graduates understand both how AI systems work and how to apply them responsibly in real projects.

What you'll study

Students typically progress from core computing topics to AI-focused subjects. Expect study areas such as:

• Foundations: programming fundamentals, data structures, algorithms, and mathematics for computing (linear algebra, probability).
• Machine learning & AI methods: supervised and unsupervised learning, neural networks, model evaluation and optimization.
• Applied AI: natural language processing, computer vision, reinforcement learning, and practical model deployment techniques.
• Systems & tools: software engineering practices, data pipelines, cloud-based tooling, model serving and API integration.
• Ethics & professional practice: algorithmic fairness, privacy, governance, and the social impact of AI systems.

Entry requirements

Entry expectations align with typical undergraduate admissions to technical bachelor's programmes: a secondary-school diploma (or equivalent) with competency in mathematics; proficiency in English; and any additional materials the university requests such as transcripts, a personal statement, and test scores if required. Prior programming experience is beneficial but not always mandatory; institutions often provide introductory courses for students new to coding.

Career prospects

Graduates with an AI concentration are positioned for roles that combine software and data skills with machine learning knowledge. Common entry-level pathways include machine learning engineer, data analyst, software developer with AI responsibilities, AI product specialist, or technical roles in industries adopting AI (healthcare, media production, entertainment technology, and business automation). Many alumni also use the undergraduate concentration as preparation for specialized graduate degrees.

Scholarships & funding angle (general)

Funding approaches for this type of programme include institutional scholarships based on academic merit or portfolio strength, need-based aid, and external scholarships from industry partners or foundations focused on STEM and AI. Prospective students should consult the university's financial aid office about tuition assistance, work-study options, and scholarship deadlines; employers and internship sponsors can also sometimes provide partial funding for students working on applied AI projects.