Applied Artificial Intelligence, AAS

GENERAL EDUCATION CORE

• MATH 123 - Quantitative Reasoning (or Higher) CREDIT HOURS MIN: 3

• ENGL 111 - English Composition CREDIT HOURS MIN: 3
• COMM 101 - Fundamentals of Public Speaking CREDIT HOURS MIN: 3

• OR

• COMM 102 - Introduction to Interpersonal Communication CREDIT HOURS MIN: 3
• XXXX XXX - Humanities /Social & Behavioral Sciences  Elective CREDIT HOURS: 3-4
• XXXX XXX - Life/Physical Science  Elective CREDIT HOURS: 3-5

OTHER INSTITUTIONAL REQUIREMENTS

• IVYT 115 - Student Success - Information Technology CREDIT HOURS MIN: 1
• CPIN 279 - Information Technology Capstone CREDIT HOURS MIN: 1

PROFESSIONAL/TECHNICAL CORE

• INFM 109 - Informatics Fundamentals CREDIT HOURS MIN: 3
• DBMS 110 - Introduction to Data Analytics CREDIT HOURS MIN: 3
• SDEV 120 - Computing Logic CREDIT HOURS MIN: 3
• SDEV 140 - Introduction to Software Development CREDIT HOURS MIN: 3
• SVAD 150 - Cloud Foundations CREDIT HOURS MIN: 3
• SDEV 220 - Software Development Using Python CREDIT HOURS MIN: 3
• AAIT 110 - Artificial Intelligence Essentials CREDIT HOURS MIN: 3
• AAIT 212 - Machine Learning CREDIT HOURS MIN: 3
• AAIT 216 - Natural Language Processing CREDIT HOURS MIN: 3
• AAIT 270 - Applied AI Projects CREDIT HOURS MIN: 3

• Pick one (1) of the following:

• AAIT 261 - AWS AI Practitioner Certification CREDIT HOURS MIN: 1
• SVAD 151 - Workforce Preparation - AWS Cloud Practitioner CREDIT HOURS MIN: 1
• SVAD 152 - Workforce Preparation - CompTia Cloud+ CREDIT HOURS MIN: 1
• SVAD 153 - Workforce Preparation - Azure Fundamentals CREDIT HOURS MIN: 1

STATEWIDE ELECTIVES

*Must complete an entire 12 credit hour track

TOTAL CREDITS: 60

Symbol Key

^ Capstone Course 

* Students must complete a track in its entireity, partial completion of multiple tracks will not complete this requirment

DEGREE OUTCOMES

• Design AI-enabled solutions that incorporate data preparation, model development, and workflow considerations to address organizational problems.
• Apply machine learning and artificial intelligence techniques using appropriate programming languages and contemporary AI frameworks.
• Analyze structured and unstructured data to generate insights that inform decision-making across functional areas.
• Evaluate ethical, security, and responsible-use considerations in AI systems, including risks, fairness implications, and compliance requirements.
• Articulate AI-driven findings, limitations, and recommendations to technical and non-technical stakeholders using professional documentation and presentation tools.
• Correlate technology’s importance in alignment and compliance with organizational policies, operational procedures, and legal requirements. 
• Construct software solutions using structured programming principles, modular design, and debugging practices to support technical system development.
• Analyze the roles and interactions of foundational cloud computing components within cloud-based system environments.