Program type:
Major
Format:
On Campus
Est. time to complete:
5 years
Credit Hours:
154
Save time and money while earning your bachelor's and master's in rapidly growing fields.
The mission of the B.A. in Information Technology is to provide an educational program that is high quality, academically challenging and career-enriching by maintaining a balance between theoretical and experimental aspects of information technology, as well as a balance between software and hardware concepts. UNT’s Artificial Intelligence master's degree is interdisciplinary, allowing students to leverage their existing skill set and experience by combining it with AI knowledge.
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Why Earn \Degrees Information Technology and Artificial Intelligence?

The B.A. in Information Technology has been ABET-accredited since 2012 and educates students about developing computer software systems in an information technology environment, such as database, network or systems administration. The program provides flexibility through concentration areas including business, game development, pre-law, security and networking, and teaching certification to become a K-12 computer science teacher.

This is an applied major focusing on topics such as database management, project management and web development. As you progress toward your degree, you'll have the opportunity to:

  • Concentrate your coursework on a focus area such as game development, business, information security, pre-law or secondary education.
  • Complete a certification from the Committee on National Security Systems.
  • Earn a certificate in game programming.

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
  • Define requirements for complex systems
  • Administer networks, sergers and databases
  • Compare alternative systems architectures
  • Teamwork
  • Web, mobile and traditional platform development
  • Code using AI programming skills
  • Design, collect, and analyze data
  • Solve problems with creative solutions
  • Quickly grasp new concepts
  • Collaborate and communicate in teams

Combined Bachelor's/Master's Information Technology and Artificial Intelligence Degrees Highlights

You'll learn from faculty members who've been recognized by the National Science Foundation, the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers.
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 is the only standalone Master of Science in Artificial Intelligence in the state of Texas and is one of few nationwide.
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.
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.
Ours is the only IT program with accreditation from the Computing Accreditation Commission (CAC) of ABET.

What Can You Do With B.A./M.S. Degrees in Information Technology and Artificial Intelligence?

Information technology applies modern technologies to creating, managing and using information. IT professionals perform duties ranging from installing applications to designing complex computer networks and information databases. Possible career opportunities include:

  • Data and information management
  • Database systems design and applications
  • Network and systems security
  • Software design and development
  • Systems and network administration and configuration
  • Teaching computer science in high schools

The most in-demand jobs in Artificial Intelligence are data scientists, software engineers, and machine learning engineers, but career opportunities can span a wide array of disciplines.

Combined Bachelor's/Master's Information Technology and Artificial Intelligence Degrees Courses You Could Take

Foundations of Data Structures (3 hrs)
Data structures and formalisms used in computing, such as asymptotic behavior of algorithms, graph, table, relational and set data structures, context-free grammars to describe patterns, assertions in propositional logic form, amortized analysis to evaluate efficiency of data structures such as splay trees and O(1) expansion of tables.
IT Project Management (3 hrs)
Provides students with the tools and techniques needed to manage a wide variety of IT systems projects, including software design and development, IT systems design and installation, network management and support, and others. Students develop and practice skills through the use of case studies and other project-based exercises.
Machine Learning (3 hrs)
The theory and process to create systems that learn directly from data to make predictions and decisions. Topics include a wide variety of supervised learning methods, both regression and classification, with an emphasis on those that perform well on large feature sets. Ensemble methods are used to combine independent approaches efficiently.
Introduction to Big Data and Data Science (3 hrs)
Introduction to Big Data and Data Science including an overview of the field, technical challenges, computational approaches, practical applications, structured and unstructured data processing, empirical methods in computer science, data analytics and learning, data visualization, privacy and ethics.
Data Mining (3 hrs)
Introduction to data mining which includes main data mining tasks, e.g. classification, clustering, association rules, and outlier detection, and some of the latest developments, e.g. mining spatial data and web data.
Foundations of Computing (3 hrs)
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.

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College of Education
Department of Computer Science and Engineering
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cse@unt.edu
Discovery Park, Room F201