Full Sail University

Programme overview

This Bachelor of Science pairs foundational computer science topics—programming, algorithms, software architecture—with concentrated study in artificial intelligence principles. The concentration emphasizes practical, project-based work to apply machine learning, pattern recognition, and intelligent systems within software development workflows. It is designed for learners aiming to design, implement, and evaluate AI-driven features in applications and media products.

What you'll study

Coursework typically covers core computer science subjects alongside AI-focused themes. Expect study areas such as programming and data structures, software engineering practices, fundamentals of machine learning and neural networks, data handling and preprocessing, and applied AI project work that integrates tools and frameworks. Instruction balances theoretical concepts with hands-on development and portfolio-building assignments.

Entry requirements

Admission ordinarily requires completion of secondary education or an equivalent credential plus any institutional application materials. Applicants should demonstrate readiness for sustained technical study; prior experience or coursework in mathematics and programming is advantageous but programmes often include introductory pathways for students without strong technical backgrounds. International applicants may need to meet additional documentation or language-proficiency criteria set by the university.

Career prospects

Graduates are prepared for technical roles where AI is used to augment products and services. Typical entry-level positions include AI developer, machine learning engineer (junior), data-focused software engineer, and roles that combine creative media production with intelligent features. Over time, professionals can specialise further into research, systems architecture, product engineering, or domain-specific AI applications in gaming, entertainment, or enterprise software.

Scholarships & funding angle (general)

Prospective students should explore institutional scholarships, merit awards, and need-based aid offered by the university, as well as external scholarships for STEM and computing disciplines. Funding strategies include applying early for institutional aid, seeking industry-sponsored grants or internships that provide tuition support, and looking into loan options and employer tuition assistance for continuing education. Building a strong application portfolio can improve competitiveness for merit-based awards.