Artificial Intelligence, M.S.
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.
Outcomes
Critically evaluate and apply foundational knowledge of AI to solve complex problems
Design, implement, and optimize intelligent systems
Effectively communicate AI capabilities and limitations to a variety of audiences
Identify and analyze emerging AI applications
Demonstrate ethical considerations in AI development
Course and Capstone Requirements
Core Courses (12 Credts):
| STAT 576 | Advanced Topics in Statistics | 3 |
| CS 544 | Machine Learning | 3 |
| CS 562 | Advanced Artificial Intelligence | 3 |
| CS 575 | Linked Data Engineering | 3 |
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 |
| CS 546/CYS 546 | Machine Learning in Cybersecurity | 3 |
| CS 547 | Deep Learning Neural Networks | 3 |
Electives (9 - 11 Credits):
Elective courses can be selected from the courses below.
| CET 529/CYS 529/CYS 429/CET 429 | Internet of Things (IoT) with Embedded Intelligence and Security | 3 |
| CS 570 | Topics in Artificial Intelligence | 3 |
| CYS 529 | Internet of Things (IoT) with Embedded Intelligence and Security | 3 |
| DATA 512 | Predictive Analytics: Estimation and Clustering | 4 |
| DATA 531 | Text Analytics with Information Retrieval | 4 |
| DATA 532 | Text Analytics with Natural Language Processing | 4 |
| STAT 467 | Applied Linear Regression Models | 3 |
CS 570 may be repeated with different topics.
Capstone Requirement (3 Credits)
| CS 596 | Capstone in Artificial Intelligence | 3 |