Artificial intelligence

The M.Engr. in artificial intelligence is a 30-credit graduate program focused on advanced AI engineering, applied problem solving and industry-driven innovation. You’ll build technical expertise in machine learning, deep learning, natural language processing, data science and intelligent systems while you prepare for leadership roles in one of the fastest-growing areas of computing.

• Explore courses in the University Catalog

Learning outcomes

The Master of Engineering (M.Engr.) requires 30 graduate credits, including 18 credits of core coursework and 12 credits in the non-thesis pathway. A thesis is not required for the M.Engr. degree, but a thesis-based M.S. option is available for students interested in research-focused study.

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 focus on applied learning through a graduate capstone project and three electives aligned with your professional interests and career goals.

Electives allow you to specialize in areas such as machine vision, adversarial machine learning, reinforcement learning, optimization and applied AI domains.

Class format

Courses are available through full-time, part-time and online options and combine advanced technical instruction, hands-on learning and collaborative project work. Students participate in:

• Applied AI model development and experimentation
• Industry-sponsored or research-driven capstone projects
• Project-based learning focused on real-world applications
• Depending on your interests, your faculty adviser will help you develop a focused plan of study.

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

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)

Find a faculty advisor

Clubs and student organizations

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 Studi
• National Society of Black Engineers (NSBE
• Robotics Club
• Society of Hispanic Professional Engineers (SHPE)
• Society of Women Engineers (SWE)
• Vandal Motorsports (SAE-Baja Competition) 

Degree roadmap

A thesis is not required for the M.Engr. degree. A thesis M.S. option is available.

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

Funding opportunities are generally not available in the form of teaching, research assistantships or fellowships to Master of Engineering (M.Engr) degree students. Consider a Master of Science degree option if funding is a concern.

Visit Financial Aid to find detailed information about the cost of attendance.

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

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

Computer Science contact:
csinfo@uidaho.edu 

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

Graduate Admissions:
graduateadmissions@uidaho.edu 
208-885-4001

Find Department of Computer Science faculty advisors

Applicants for the Master’s of Engineering in artificial intelligence must meet the following admission requirements:

Program availability

• Concentration: Non-thesis
• Semester intake: Spring and Fall
  • Eligible for 4+1 admission
  • Eligible for expedited admission for U of I undergraduates
  • 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
•  For additional details, please visit the General application deadlines
• 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.  (for applicants whose education was completed in countries where English is not an official language)
• 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.