Program type:


On Campus
Est. time to complete:

2 years
Credit Hours:

Will you be responsible for the next great leap in autonomous systems?
Advancements in robotics, self-driving vehicles and unmanned aircraft have turned ideas that used to be science fiction into reality. Our master's in Artificial Intelligence with a concentration in Autonomous Systems will help you become an innovator in this exciting field.

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Why Earn a degree in Autonomous Systems Artificial Intelligence?

UNT’s Artificial Intelligence master's degree with a concentration in Machine Learning is interdisciplinary, allowing students to leverage their existing skill set and experience by combining it with AI knowledge. This is a STEM-designated master's program.

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.
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

Autonomous Systems Artificial Intelligence Master's Highlights

The College of Engineering has state-of-the-art instructional facilities and laboratories containing cutting-edge research equipment in top-ranked research labs that offer exciting possibilities for study and discovery.
Alongside faculty members, you’ll prepare you for the most in-demand AI jobs by exploring areas of study such as autonomous systems, biomedical engineering, machine learning and natural language processing.
Core courses will dive into deep learning, machine learning, big data and data science, and feature engineering.
Bridge courses provide you the necessary background in programming and include Software Development for Artificial Intelligence and Fundamentals of Artificial Intelligence.
Teaching and research assistantships are available to help you pursue your graduate degree by providing you with a monthly stipend and may qualify you for in-state tuition rates.
This is the only stand alone Master of Science in Artificial Intelligence in the state of Texas and is one of few worldwide.

What Can You Do With A Degree in Autonomous Systems Artificial Intelligence?

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.

Autonomous Systems Artificial Intelligence Master's Courses You Could Take

Deep Learning (3 hrs)
Hands-on​ ​introduction​ ​to​ ​deep​ ​learning emphasizing application using GPU-accelerated hardware to train multilayer machine learning models directly on raw input signals. Discuss​es ​the foundations​ ​of​ ​feedforward​ ​networks,​ ​convolutional​ ​neural networks,​ ​and​ ​recurrent​ ​networks,​ ​as​ ​well​ ​as​ ​their usage​ ​within​ ​popular​ ​reinforcement​ ​learning​ ​frameworks.
Systems Modeling and Simulation (3 hrs)
Aims to systematically introduce the concepts and analytical tools required to abstract engineering problems from applications, and to simulate and analyze such problems. Topics include dynamical systems modeling, stochastic models, queuing models, Markov chains, model identification, Monte-Carlo simulation, model reduction, agent-based modeling, large-scale networks, and applications to ecological, biological, and modern infrastructure systems.
Control Systems Design (3 hrs)
Transform domain and state space representations of linear feedback systems, system stability, nonlinear systems, optimal control, bounded and time optimal control of linear systems.
Computer Vision and Image Analysis (3 hrs)
Introduction to computer vision and image processing, image geometry and photogammetry, edge detection, feature extraction, shape representation, structural descriptions, object modeling, shape matching, semantic knowledge bases and imaging architectures, depth perception with stereo and photometric stereo, moving scene analysis and object tracking, multi-sensor data fusion, occluded object recognition by multi-sensor/multi-view integration, Computer Vision applications.
Digital Signal Processing (3 hrs)
Introduction to modern digital signal processing theory and techniques. Includes discrete time signals and systems, sampling theorem, Z-transform, frequency analysis of signals and systems, discrete Fourier transform, fast Fourier transform algorithms, and digital filter design.
Software Development for Artificial Intelligence (3 hrs)
New programming paradigms are needed to create and manage systems with embedded AI capabilities. Students are taught how to leverage available artificial intelligence APIs flexibly and reliably. Additionally, as data management is integral to AI system development, an emphasis is made to collect and process data for AI system training and testing.

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