Combined B.S./M.S. Computer Science and Artificial Intelligence Degrees

Program type:

Major

Graduate Academic Certificate

Format:

On Campus

Est. time to complete:

5-6 years

Credit Hours:

153

Accelerate your education with UNT and harness in-demand computer science skills for deep learning, machine learning, data science and feature engineering.

If you're good at multi-tasking, have strong computer skills and are familiar with the latest computer software and hardware, you should consider pursuing a Bachelor of Science degree in Computer Science. Computer scientists enjoy some of the highest salaries of any engineering profession, and you can use your skills to find solutions using the latest technology. Students interested in the exciting field of artificial intelligence can apply for UNT Engineering’s graduate track program. This pathway will help you transition into graduate coursework while working on your undergraduate degree in Computer Science. Our Artificial Intelligence program offers the only standalone Master of Science in Artificial Intelligence in the state of Texas. UNT’s degree is interdisciplinary, allowing students to leverage their existing skillset 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.

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Why Earn a combined B.S./M.S. degree in Computer Science and Artificial Intelligence?

The Department of Computer Science and Engineering provides high quality educational programs by maintaining a balance between theoretical and experimental aspects of computer science, as well as a balance between software and hardware issues, and by providing curricula that serve the citizens and industrial organizations of Texas in general, and those in North Texas in particular.

The Bachelor of Science degree with a major in computer science is a professional degree designed to prepare the student for a career of further studies in the technology and application of computers.

The graduate track program allows students to take graduate coursework while earning their bachelor's degree so they can save time and money on their education, transition into their graduate studies and achieve their career goals sooner.

The AI program is designed to meet the needs of our students and industry; students will graduate with marketable skills in programming, data analysis, problem solving and communication. 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:

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

The College of Engineering has state-of-the-art instructional facilities and laboratories containing cutting-edge research equipment. Top-ranked research labs offer exciting possibilities for study and discovery. Alongside faculty members, you’ll explore areas of study that will prepare you for the most in-demand AI jobs.

Marketable Skills

Analyze the complexity of an algorithm
Use data structures in software design
Compare algorithm merits
Teamwork
Learn a programming language
Code using AI programming skills
Design, collect, and analyze data
Solve problems with creative solutions
Quickly grasp new concepts
Collaborate and communicate in teams

Computer Science and Artificial Intelligence Highlights

Classes and research are conducted at Discovery Park, a 300-acre research facility located five miles north of the main campus and serviced by a free shuttle. This research facility joins academic laboratories, offices and classrooms to maximize the potential for creativity, collaboration and technology innovation.

In addition to instructional facilities with cutting-edge equipment, the department supports numerous centers and research laboratories that offer unlimited possibilities for study and research.

UNT is located in Denton, TX, a college town that part of the Dallas-Fort Worth metropolitan area. DFW is the country’s fourth-largest metropolitan area and offers a wealth of job opportunities as well as entertainment, culture and more.

Our Living Learning Community brings together engineering students who live on campus to enhance academic and social experiences.

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. The College of Engineering also offers scholarships to qualified students throughout the year.

Our students prepare for computer science and engineering careers that solve societal problems, advance technology and improve the quality of life for people everywhere.

Computer Science and Artificial Intelligence Courses You Could Take

Conceptual and formal models, efficiency and levels of abstraction as used in the field of computing, big-Oh notation, combinatorics and conditional probability, basic operations of sets, functions, relations, trees and graphs, regular expressions, deterministic finite automata and non-deterministic finite automata to describe patterns in strings.

Time complexity of algorithms; merge sort and heap sort; data structures for trees and graphs; elementary graph algorithms; breadth-first search; depth-first search; topological sorting; Prim’s algorithm and Kruskal’s algorithm.

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.

Focused on applied signal processing across a variety of modalities including still images and video, audio signals, sensor signals, and natural extensions to other rich multidimensional signals. Students are introduced to computer and simplified biological visual and auditory processing models. This includes signal transduction, edge detection and segmentation. Spectral representations include fourier and various wavelet decompositions useful in making inferences from signals.

Study of the fundamentals of pattern recognition techniques including Bayesian decision and estimation, non-parametric methods, multi-class classifiers and feature selection methods.

Introduction to computer science and engineering, problem-solving techniques, algorithmic processes, software design and development.