The University of Texas at Dallas

How this program compares

At an estimated $37.5K in total tuition, the MS in Artificial Intelligence for Biomedical Sciences sits roughly 13% below the $42.9K average for AI master's programs in our database — placing it in the 57th percentile on cost among the 394 we track at this level. It runs on a full-time, part-time schedule (on-campus).

Admission Snapshot

Typical admitted student: A bachelor's degree in computer science, engineering, mathematics, or a related field is required, along with a minimum GPA of 3.0. Applicants should have foundational knowledge in programming, statistics, and mathematics.

About This Program

This program bridges the gap between computer science and healthcare, training students to apply advanced AI techniques to complex biomedical and clinical data. Coursework concentrates on Machine Learning and Deep Learning. Most students complete it in about 1 year.

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 61% of the Texas programs in our data, where typical tuition runs near $41.5K.

Graduates frequently move into roles such as Data Scientist, with reported salaries around $130,000.

Apply machine learning algorithms to solve complex biomedical problems and clinical decision-making.

Estimated total tuition is $37.5K, below the $42.9K average for AI master's programs in our database and in the 57th percentile on cost at this level. That puts it in the mid-range on price among comparable programs.

Career Outcomes

Graduates of The University of Texas at Dallas's MS in Artificial Intelligence for Biomedical Sciences most often target Data Scientist roles, where reported compensation runs around $130,000. Its focus on Machine Learning and Deep Learning maps directly to how employers in healthcare ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 36% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Machine Learning Engineer (Healthcare/Biotech)
• 2. Biomedical Data Scientist
• 3. Clinical Informatics Specialist
• 4. AI Research Scientist (Medical Institutions)

What You'll Learn

• Apply machine learning algorithms to solve complex biomedical problems and clinical decision-making
• Develop and deploy deep learning models for medical imaging, diagnostics, and predictive analytics
• Analyze large-scale health datasets and implement data science solutions in healthcare settings
• Design ethical AI systems that address privacy, bias, and regulatory compliance in biomedical research

Curriculum Highlights

The curriculum features coursework in machine learning, epidemiology, clinical decision support, and natural language processing specifically for the healthcare and biomedical industries.

Top Employers

Common employers include major healthcare organizations like Mayo Clinic, Cleveland Clinic, and major pharmaceutical companies such as Pfizer and Johnson & Johnson, as well as biotech firms and health tech startups.

Admissions

Admission to The University of Texas at Dallas's MS in Artificial Intelligence for Biomedical Sciences generally expects a master of science (ms). Plan for the GRE, which this program lists as required. 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