The University of Texas at Dallas

How this program compares

At an estimated $39.6K in total tuition, the MS in Systems Engineering & Management - AI and Machine Learning Concentration sits roughly 8% below the $42.9K average for AI master's programs in our database — placing it in the 59th percentile on cost among the 394 we track at this level. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: A bachelor's degree in engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with relevant coursework in programming, mathematics, and systems analysis. Work experience in engineering or AI is preferred but not mandatory.

About This Program

A master's degree program that bridges the gap between technical AI knowledge and strategic management skills to prepare graduates for leadership in multidisciplinary teams. Coursework concentrates on Machine Learning and AI Engineering / Applied AI. Most students complete it in about 2 years.

It is one of 45 AI-related programs we track in Texas, of which about 51% offer an online option. On price, it comes in higher than about 66% of the Texas programs in our data, where typical tuition runs near $41.5K.

Graduates frequently move into roles such as AI Engineer, with reported salaries around $125,000.

Design scalable AI systems integrating engineering and machine learning components.

At roughly $39.6K total, The University of Texas at Dallas's MS in Systems Engineering & Management - AI and Machine Learning Concentration sits below the $42.9K average among AI master's programs we track — the 59th percentile on price. That puts it in the mid-range on price among comparable programs.

Career Outcomes

The University of Texas at Dallas positions this master track for AI Engineer careers — typical offers cluster around $125,000. Its focus on Machine Learning and AI Engineering / Applied AI maps directly to how employers in engineering ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 23% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. AI Systems Engineer
• 2. ML Operations Engineer
• 3. Systems Integration Specialist - AI
• 4. AI Reliability Engineer

What You'll Learn

• Design scalable AI systems integrating engineering and machine learning components.
• Deploy and monitor production-grade ML models with reliability focus.
• Optimize systems using advanced AI techniques like deep learning and optimization.
• Manage data pipelines and feature engineering for real-world AI applications.

Curriculum Highlights

The 36-hour STEM program includes core engineering and management coursework with a concentration in AI and applied machine learning systems.

Top Employers

Top employers include tech firms like Google, Amazon, Microsoft, and defense contractors such as Lockheed Martin and Raytheon.

Admissions

Admission to The University of Texas at Dallas's MS in Systems Engineering & Management - AI and Machine Learning Concentration generally expects a bachelor's degree. The GRE is optional here — a growing norm among AI programs — so applicants can often lead with coursework, projects and recommendations instead. Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2–3
• Resume: Required
• Transcripts: Official transcripts required

Frequently Asked Questions