Artificial intelligence

The Master of Science in artificial intelligence is a 30-credit, research-focused graduate program combining advanced coursework with independent research and applied learning experiences. This degree can be completed in person or online. You’ll build technical expertise in machine learning, deep learning, reinforcement learning, optimization and applied data science while gaining hands-on experience developing intelligent systems that address real-world challenges. Working alongside faculty mentors, you’ll explore areas such as natural language processing, AI ethics, predictive modeling and large-scale computing systems through interdisciplinary research and thesis work. The program prepares you to contribute to emerging AI technologies across industries including healthcare, cybersecurity, agriculture, energy, robotics and advanced manufacturing while strengthening your ability to conduct research, communicate technical findings and lead innovation in the rapidly evolving field of artificial intelligence.

• Explore program courses in the University Catalog

Degree roadmap

A thesis is required for the M.S. degree. A non-thesis M.Engr. option is available.

• This program may also be completed part-time or online through Engineering Outreach.
• Depending on your interests, your faculty advisor will help you develop a focused plan of study.

Learning outcomes

The Master of Science (M.S.) in Artificial Intelligence requires 30 graduate credits, including advanced core coursework and a research-based thesis. Designed for students interested in research, innovation and doctoral study, the program combines technical depth with independent investigation into emerging artificial intelligence technologies and applications.

Core coursework establishes advanced competencies in:

• Python for machine learning
• Artificial intelligence and deep learning
• Natural language processing
• Data science and applied AI
• AI governance
• Ethics and professional responsibility

After completing core requirements, you’ll work closely with your major professor to develop a focused plan of study aligned with your research interests and professional goals. Through thesis research and elective coursework, you can specialize in areas such as machine vision, adversarial machine learning, reinforcement learning, optimization, trustworthy AI and applied AI domains.

Class format

Courses are available through full-time, part-time and online options and combine advanced technical instruction, research-driven learning and collaborative project work. As a student, you’ll participate in:

• Applied AI model development and experimentation
• Research-focused projects and thesis work
• Project-based learning centered on real-world applications
• Interdisciplinary collaboration across engineering and computing fields

Program faculty and student involvement

Faculty areas of emphasis include:

• AI and cybersecurity
• Industrial robotics
• Trustworthy AI
• Deep learning
• Machine learning
• Multi-agent systems
• Secure AI
• Quantum machine learning
• Computer vision and NLP
• IoT and cyber-physical systems

Find a faculty advisor. You can also connect with peers and expand your experience through engineering-focused clubs and organizations, including:

• Cyber Defense Club
• CyberForce Competition Team
• Graduate and Professional Student Association (GPSA)
• Humanitarian Engineering Corps (HEC)
• Polymorphic Games Studio
• National Society of Black Engineers (NSBE)
• Robotics Club
• Society of Hispanic Professional Engineers (SHPE)
• Society of Women Engineers (SWE)
• Vandal Motorsports (SAE-Baja Competition)

Funding is competitive and faculty may provide graduate funding through a variety of external agencies and industry partners. Contact our faculty to learn more about these funding opportunities or explore graduate fellowship programs.

Recognized STEM Program

This program is recognized as a STEM program by the U.S. Department of Homeland Security and may be eligible for the 24-month STEM optional practical training extension for international students.

Learn more about STEM approved CIP/degree codes

University of Idaho is committed to making graduate education accessible and helping students navigate the cost of earning an advanced degree. In addition to financial aid and scholarship opportunities, many graduate students receive funding through assistantships, research opportunities and other forms of academic support.

Here are a few key resources to help you understand graduate tuition, funding opportunities and available financial support:

• Submit your FAFSA: Completing the Free Application for Federal Student Aid (FAFSA) is an important first step in accessing federal financial aid and certain institutional funding opportunities.
• Estimate your cost of attendance: Visit U of I’s cost of attendance page to explore estimated tuition, fees and living expenses associated with your graduate program.
• View a breakdown of tuition and fees: Visit the Student Accounts page to explore current tuition rates, fees and detailed cost information based on your program, residency status and enrollment level.
• Explore scholarships and graduate funding opportunities: Graduate students may qualify for scholarships, fellowships and other funding opportunities based on academic achievement, area of study and professional experience.
• Learn about assistantships: Many graduate programs offer Research Assistantships (RAs), Teaching Assistantships (TAs) or Graduate Assistantships (GAs), which may provide tuition support, stipends and valuable professional experience. Assistantship availability and funding levels vary by program and department.
• Connect with your program: Some graduate funding opportunities are coordinated directly through academic departments or faculty research projects. Prospective students are encouraged to review department funding information and speak with program representatives about available opportunities.

If you have questions about financial aid, scholarships or graduate funding, U of I’s experienced financial aid counselors and graduate program staff can help you explore options and make informed financial decisions throughout the admissions process.

View financial aid resources

Have questions about the program, research opportunities or the graduate student experience? Connect with our program team for personalized assistance about curriculum, faculty guidance, application requirements and graduate funding opportunities.

Computer science contact:
csinfo@uidaho.edu

For questions related to admissions, application materials, transcripts or enrollment steps, contact Graduate Admissions.

Graduate admissions contact:
graduateadmissions@uidaho.edu
208-885-4001

Interested in research areas or finding a major professor? Explore faculty expertise, research interests and advising opportunities on the department’s faculty page.

Find Department of Computer Science faculty

Applicants for the artificial intelligence M.S. must meet the following admission requirements:

Program availability

• Concentration: Non-thesis
• Semester intake: Spring and Fall
  • Not eligible for international applicants who require F-1 or J-1 visa status
• Deadlines: This program offers rolling admissions with the following recommended application deadlines:
  • Fall applications: July 30
  • Spring applications: November 1
• Start dates:  
  • View the academic calendar to see start and end dates

University requirements

• Education level: Bachelor's degree in a related or similar field
  • Transcripts for all post-secondary education will be required. Unofficial transcripts may be used for initial admission review. View more information on the Graduate Admissions page.
• GPA: 3.0 (Applicants with a lower undergraduate GPA who have relevant professional experience in the field, have already earned a graduate degree, or have completed graduate-level credits may still be considered for admission with approval from the academic program.)
• GRE: No
• TOEFL/IELTS/Duolingo/PTE-A: 4.5/6.5/115/58.  (Learn what qualifies as proof as English proficiency)
• Number of references: Three academic or professional references
• Other requirements:
  • Resume
  • Statement of Purpose (SOP)

Visit Graduate Admissions to learn more and start your application.