University of North Texas 
Artificial Intelligence, MS
Considering a career in the exciting field of artificial intelligence? UNT Engineering's new graduate program may be just the answer. It's the only standalone Master of Science in Artificial Intelligence in the state of Texas and is one of few nationwide.
UNT's degree is interdisciplinary, allowing students to leverage their existing skill set and experience by combining it with AI knowledge. Graduate students in our program have the opportunity to specialize in machine learning, biomedical engineering, or autonomous systems. This is a STEM-designated master's program.
According to the World Economic Forum, jobs in AI will grow by 58 million between 2018 and 2022, and Indeed.com reports employer demand for these roles has doubled in the past three years.
What to Expect
Students can expect to take 6 hours of bridge courses, 15 hours of core courses, and 12 hours of in their chosen concentration.
Bridge courses give students the necessary background in programming and include Introduction to Programming in Artificial Intelligence and Foundations of Artificial Intelligence.
Core courses will dive into deep learning, machine learning, big data and data science, and feature engineering.
Concentration areas focus on machine learning, biomedical engineering, and autonomous systems, offering students the opportunity to choose their own career path.
Students who graduate from this program will be able to:
- Understand and apply the concepts of programming related to AI
- Identify and implement AI applications to solve problems
- Create and utilize AI systems that respond to market needs
- Analyze and apply AI concepts and applications available in their chosen field of interest
- Understand the business needs and job market in AI
Course Offerings
Bridging and Core Courses | 18 Hours (Required for all students)
| Course | Credit Hours |
|---|---|
| CSCE 5214: Software Development for Artificial Intelligence | 3 |
| CSCE 5210: Fundamentals of Artificial Intelligence | 3 |
| CSCE 5218: Deep Learning | 3 |
| CSCE 5215: Machine Learning | 3 |
| CSCE 5222: Feature Engineering | 3 |
| CSCE 5300: Introduction to Big Data and Data Science | 3 |
Validation and Testing Courses | 3 Hours (Choose one based on your concentration)
| Course | Credit Hours |
|---|---|
| CSCE 5310: Methods in Empirical Analysis | 3 |
| BMEN 5007: Research Methods in Biomedical Engineering | 3 |
| EENG 5320: Systems Modeling and Simulation | 3 |
| MEEN 5140: Advanced Mathematical Methods for Engineers | 3 |
Machine Learning Concentration | 12 Hours (Students choose 4 courses from the list below)
| Course | Credit Hours |
|---|---|
| CSCE 5290: Natural Language Processing | 3 |
| CSCE 5380: Data Mining | 3 |
| CSCE 5200: Information Retrieval and Web Search | 3 |
| CSCE 5216: Pattern Recognition | 3 |
| CSCE 5320: Scientific Data Visualization | 3 |
| CSCE 5280: AI for Wearables and Healthcare | 3 |
| CSCE 5900: Special Problems | 3 |
Biomedical Engineering Concentration | 12 Hours (Students choose 4 courses from the list below)
| Course | Credit Hours |
|---|---|
| BMEN 5322: Medical Imaging | 3 |
| BMEN 5005: Neuroengineering | 3 |
| BMEN 5324: Biomedical MEMs | 3 |
| BMEN 5310: Clinical Instrumentation | 3 |
| BMEN 5900: Special Problems | 3 |
| EENG 5640: Computer Vision and Image Analysis | 3 |
| CSCE 5216: Pattern Recognition | 3 |
| CSCE 5225: Digital Image Processing | 3 |
Autonomous Systems Concentration | 12 Hours
| Course | Credit Hours |
|---|---|
| EENG 5640: Computer Vision and Image Analysis | 3 |
| EENG 5310: Control Systems | 3 |
| EENG 5610: Digital Signal Processing | 3 |
| EENG 5900: Special Problems | 3 |
Choose Your Career Path
The most in-demand jobs are data scientists, software engineers, and machine learning engineers, but career opportunities in artificial intelligence can span a wide array of disciplines. If you envision yourself in the healthcare industry, then a concentration in biomedical engineering could be perfect. If robotics, self-driving vehicles, or drones are more your speed, then a path in machine learning or autonomous systems could open an exciting field for you. Whichever route you choose, the marketable skills you'll receive from this program are sure to prepare you for a challenging career in AI.
Marketable Skills
- Code using AI programming skills
- Design, collect, and analyze data
- Solve problems with creative solutions
- Quickly grasp new concepts
- Collaborate and communicate in teams
Admissions
Our program is open to high-achieving students from engineering, computer science, math, and science-related backgrounds. Each applicant's transcripts will be reviewed to determine if their background is suitable for admission into the concentration of their choice and/or if leveling coursework is required. If leveling coursework is needed, students may be required to take undergraduate leveling courses to prepare for coursework in the concentration of their choice.
Applicants for this program should:
- Have a minimum 3.0 cumulative GPA in previous coursework
- Have taken statistics or linear algebra and have prior programming experience using languages like C++, Java,Python, R, or Matlab
- Submit transcripts and GRE scores. GRE may be waived for graduates of UNT.
- International applicants should submit TOEFL or IELTS scores.
- Submit a resumé (optional)
Send email to CENG.GradAdmissions@unt.edu for more information.
Apply by January 15th to be considered for all funding opportunities.
Funding Your Degree
Teaching and research assistantships provide support for many graduate students. In addition to a monthly stipend, assistantships also qualify students for in-state tuition rates, and many students receive tuition and fee support. Scholarships are available to graduate students as well. The general scholarship deadline is March 1 of each year. The College of Engineering also offers scholarships to qualified students throughout the year.
For more information about tuition, visit the online tuition calculator.