The Master of Science in Artificial Intelligence will provide students with a comprehensive understanding of AI concepts, algorithms, and applications, preparing them for exciting and challenging careers in the rapidly growing field of artificial intelligence. Graduates of this program will be equipped to pursue various career paths in industries such as technology, healthcare, finance, gaming, and automation.
Prerequisite | ||
| (Students may take a proficiency exam or complete this course offered Winter Mini or August Mini) | ||
| CSCI 513 | Python Programming for AI | 3 |
Thesis (6 semester hours required) | ||
| CSCI 518 | Thesis (6 semester hours required) | 3-6 |
| Core Courses (19 semester hours) | ||
| AI 500 | Foundations of Artificial Intelligence | 4 |
| AI 510 | Seminar in Artificial Intelligence Ethics | 3 |
| CSCI 527 | Data Mining | 3 |
| CSCI 576 | Computer Vision | 3 |
| AI 520 | Machine Learning for Artificial Intelligence | 3 |
| ENG 685 | Symbolic Computational Linguistics | 3 |
| Students must complete one of the following: (12 semester hours) | ||
Computer Science Emphasis (12 semester hours) | ||
| CSCI 556 | Data Analysis & Visualization | 3 |
| CSCI 560 | Neural Networks and Deep Learning | 3 |
| CSCI 573 | Big Data Computing and Analytics | 3 |
| CSCI 503 | Trusted Artificial Intelligence and Autonomous Systems | 3 |
English Emphasis (12 semester hours) | ||
| ENG 555 | General Linguistics | 3 |
| ENG 562 | Psycholinguistics | 3 |
| ENG 682 | Machine Learning for Linguists | 3 |
| ENG 683 | Algorithm Design for Linguists | 3 |
Mathematics Emphasis (12 semester hours) | ||
| MATH 531 | Theory of Matrices | 3 |
| MATH 546 | Numerical Analysis and Elements of Machine Learning | 3 |
| MATH 563 | Image Processing with Elements of Learning | 3 |
| MATH 569 | Image Analysis and Recognition with Learning | 3 |
Psychology Emphasis (12 semester hours) | ||
| PSY 511 | Cognitive Science | 3 |
| PSY 620 | Intro to Human Cognition | 3 |
| PSY 626 | Cognition/Instruction II | 3 |
| PSY 645 | Introduction to Learning Technology | 3 |
| Total Hours | 37 | |
Prerequisite | ||
| (Students may take a proficiency exam or complete this course offered Winter Mini or August Mini) | ||
| CSCI 513 | Python Programming for AI | 3 |
Research (3 semester hours) | ||
| CSCI 595 | Research Literature and Techniques (3 semester hours required) | 3 |
Core Courses (19 semester hours) | ||
| AI 500 | Foundations of Artificial Intelligence | 4 |
| AI 510 | Seminar in Artificial Intelligence Ethics | 3 |
| CSCI 527 | Data Mining | 3 |
| CSCI 576 | Computer Vision | 3 |
| AI 520 | Machine Learning for Artificial Intelligence | 3 |
| ENG 685 | Symbolic Computational Linguistics | 3 |
| Students must complete one of the following: (12 semester hours) | ||
Computer Science Emphasis (12 semester hours) | ||
| CSCI 556 | Data Analysis & Visualization | 3 |
| CSCI 560 | Neural Networks and Deep Learning | 3 |
| CSCI 573 | Big Data Computing and Analytics | 3 |
| CSCI 503 | Trusted Artificial Intelligence and Autonomous Systems | 3 |
Engilish Emphasis (12 semester hours) | ||
| ENG 555 | General Linguistics | 3 |
| ENG 562 | Psycholinguistics | 3 |
| ENG 682 | Machine Learning for Linguists | 3 |
| ENG 683 | Algorithm Design for Linguists | 3 |
Mathematics Emphasis (12 semester hours) | ||
| MATH 531 | Theory of Matrices | 3 |
| MATH 546 | Numerical Analysis and Elements of Machine Learning | 3 |
| MATH 563 | Image Processing with Elements of Learning | 3 |
| MATH 569 | Image Analysis and Recognition with Learning | 3 |
Psychology Emphasis (12 semester hours) | ||
| PSY 511 | Cognitive Science | 3 |
| PSY 620 | Intro to Human Cognition | 3 |
| PSY 626 | Cognition/Instruction II | 3 |
| PSY 645 | Introduction to Learning Technology | 3 |
| Total Hours | 34 | |
