The University of Texas at Austin

How this program compares

Budget-wise, $97.0K puts this bachelor's program at the 67th percentile on cost — about 8% above the $89.8K average across 186 comparable listings. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: High school diploma or GED with strong background in mathematics and science. Most competitive CS programs with AI concentration require a minimum GPA of 3.5, SAT scores of at least 1300 (or ACT equivalent), and demonstrated interest in computer science through coursework or programming experience.

About This Program

This undergraduate concentration equips computer science majors with specialized skills in designing and training intelligent systems and machine learning models. Coursework concentrates on Natural Language Processing (NLP) and Computer Vision. Most students complete it in about 4 years.

Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $128,000.

Design and implement machine learning models using supervised and unsupervised learning techniques.

Budget planners should note $97.0K estimated total tuition (67th percentile among AI bachelor's programs, above the $89.8K average). Applicants should weigh that premium against the program's outcomes and brand.

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 91% of the Texas programs in our data, where typical tuition runs near $41.5K.

Career Outcomes

Graduates of The University of Texas at Austin's BA/BS/BSA in CS – ML & AI Concentration most often target Machine Learning Engineer roles, where reported compensation runs around $128,000. Its focus on Natural Language Processing (NLP) and Computer Vision maps directly to how employers 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
• 2. AI Software Engineer
• 3. Data Scientist
• 4. Computer Vision Engineer

What You'll Learn

• Design and implement machine learning models using supervised and unsupervised learning techniques
• Develop deep learning architectures including neural networks, convolutional networks, and recurrent networks
• Apply AI and NLP techniques to solve real-world problems in data analysis and prediction
• Understand ethical considerations in AI development, including bias detection, fairness, and responsible AI practices

Curriculum Highlights

The curriculum features a 12-credit-hour focus including foundation courses in AI or data mining, followed by electives in neural networks and robotics.

Top Employers

Top employers include Google, Microsoft, Meta, Amazon, Apple, Tesla, OpenAI, and major tech firms specializing in artificial intelligence and machine learning systems.

Admissions

Admission to The University of Texas at Austin's BA/BS/BSA in CS – ML & AI Concentration generally expects a bachelor of science. The GRE is not required 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

• High School Transcripts: Official transcripts required
• Standardized Test Scores: SAT/ACT scores required
• Resume: Optional
• Essays: 1–2 essays demonstrating interest in technology and computer science
• Letters of Recommendation: 2 from academic or technical sources

Frequently Asked Questions