University of North Texas

How this program compares

Benchmark this program against our national recognition pages and use the key guides below to evaluate ROI, admissions difficulty, and outcomes.

Admission Snapshot

Typical admitted student: Maintain a 3.0 cumulative GPA after the first semester with probation rules as stated in the catalog; grades of B or better are required in core, bridge, and validation courses. Confirm undergraduate prerequisites and international credential rules with the admitting program office.

About This Program

UNT publishes this degree as a face-to-face interdisciplinary master’s spanning computer science and engineering units, designed around explicit AI bridge and core sequences plus concentration-specific research or professional depth.

Career Outcomes

Interdisciplinary MS with bridge coursework, ML/deep learning cores, and concentrations in machine learning, biomedical engineering, or autonomous systems.

• 1. Machine Learning Engineer
• 2. AI Software Engineer
• 3. Robotics / Autonomy Engineer
• 4. Biomedical AI specialist

What You'll Learn

• Complete shared AI foundations before advanced core ML and deep learning study.
• Satisfy validation-methods expectations tied to the chosen concentration.
• Pursue thesis research or additional coursework under the course-only path.
• Access concentration electives in NLP, data mining, vision, controls, or biomedical instrumentation depending on track.

Curriculum Highlights

UNT’s catalog describes the MS with a major in artificial intelligence as interdisciplinary, with thesis (30 hours including 6 thesis hours) and course-only (33 hours) options. Six hours of bridge courses (Fundamentals of AI; Software Development for AI) precede core work. Non-thesis students complete 12 hours of core courses including machine learning, deep learning, feature engineering, and intro to big data/data science; thesis students complete 9 hours of those core courses excluding big data per the published structure. Each student selects a concentration—machine learning, biomedical engineering, or autonomous systems—totaling 12 hours including a concentration-specific validation methods course. Elective and thesis credit rules follow the Department of Computer Science and Engineering listings.

Top Employers

Dallas–Fort Worth metro and Texas-wide technology employers recruit engineering-heavy AI graduates; verify placement via UNT official disclosures.

Admissions

Maintain a 3.0 cumulative GPA after the first semester with probation rules as stated in the catalog; grades of B or better are required in core, bridge, and validation courses. Confirm undergraduate prerequisites and international credential rules with the admitting program office.

Application Materials

• Statement of purpose: Required (typical)
• Letters of recommendation: Confirm count
• Resume: Required
• Transcripts: Official transcripts required

Academic Requirements

• Degree Required: Bachelor's (engineering/CS-related typical)
• GRE/GMAT: Verify current cycle
• TOEFL/IELTS: Per UNT graduate policy for international applicants