This is an unofficial description for this program. For official information check the Academic Catalog.
Program is pending final approval by the Board of Regents.
The Master of Science in Artificial Intelligence program equips students with the knowledge and skills to design, develop, and implement intelligent systems. This program is designed for individuals with a strong computer science background and prepares graduates for exciting careers in a rapidly growing field.
The curriculum balances foundational concepts with practical applications. Core courses cover essential topics like artificial intelligence, machine learning, data science, and knowledge representation. Students then delve deeper by choosing electives in areas such as deep learning, machine learning for cybersecurity, generative AI, natural language processing, or predictive analytics. A culminating capstone project allows students to apply their learned skills to a real-world artificial intelligence problem. This program is ideal for those seeking to become leaders in the field of artificial intelligence and make a significant impact on the ever-evolving technological landscape.
Course and Capstone Requirements
Core Courses (12 Credts):
Extended Core Courses (6 Credits):
For the extended core courses, pick any two of the following courses.
CS 545 Machine Learning for Data Mining 3 Credits
Electives (9 - 11 Credits):
Elective courses can be selected from the courses below.
CET 529 Internet of Things (IoT) with Embedded Intelligence and Security 3 Credits
CS 570 Topics in Artificial Intelligence 3 Credits
CYS 529 Internet of Things (IoT) with Embedded Intelligence and Security 3 Credits
DATA 512 Predictive Analytics: Estimation and Clustering 4 Credits
DATA 531 Text Analytics with Information Retrieval 4 Credits
DATA 532 Text Analytics with Natural Language Processing 4 Credits
CS 570 may be repeated with different topics.