The University of Texas at Austin ranks among the 10 most cost-effective schools for college graduates pursuing careers at major tech companies, according to a new study.

The study, conducted by data science education platform DataCamp and sent directly to reporters, analyzed the 20 universities at the top of the QS World Universities list for Computer Science and Information Systems.

Researchers examined the number of grads working at five major tech companies — Amazon, Apple, Google, Meta, and Microsoft — compared with the annual cost of attendance. Job data was gathered via LinkedIn, and tuition data came from College Scorecard.

UT lands at No. 9 in the study, with 6,598 graduates working at top tech employers and an annual cost of attendance at $18,850. The University of Washington claims the No. 1 ranking in the study, with 14,745 grads working at top tech employers and an annual cost of attendance totaling $12,777.

UT was the only Texas institution included in the study.

DataCamp and QS are not the only organizations looking to UT for computer science skills. U.S. News & World Report puts UT in:

• Sixth place for analytics (undergraduate)
• Seventh place for management information systems (undergraduate)
• Seventh place for AI (undergraduate)
• Eighth place for computer engineering (undergraduate)
• Ninth place for computer science (undergraduate)
• Ninth place for computer science theory (undergraduate)
• A seventh-place tie for computer science (graduate)
• Seventh place for computer science theory (graduate)
• Eighth place for programming language (graduate)
• 10th place for AI (graduate)
• 11th place for computer systems (graduate)

Research.com also awards a No. 10 national ranking to the university’s computer science program, and CSRankings puts it at No. 13.

UT is making great strides in the super-hot AI field. In November, the university announced it had doubled the computing capacity of the Center for Generative AI, which is available only to UT faculty and student researchers. The center ranks among the world’s most powerful AI hubs in academia.

The scale of the center’s computing cluster “will allow us to create solutions to bigger real-world problems that make a difference in people’s lives,” said Adam Klivans, director of the UT-led National Science Foundation Institute for Foundations of Machine Learning, in a press release when the capacity increase was announced. "It’s exciting to accelerate discovery and to create more opportunities for our researchers to push the boundaries of what’s possible.

The top 10 schools by cost effectiveness, according by DataCamp, are:

• 1. University of Washington: $12,777
• 2. Stanford University: $10,851
• 3. Georgia Institute of Technology: $14,588
• 4. University of California, Berkeley: $17,371
• 5. University of California, Los Angeles: $15,637
• 6. University of Illinois at Urbana-Champaign: $16,109
• 7. Princeton University: $8,143
• 8. University of California, San Diego: $15,069
• 9. University of Michigan: $16,792
• 10. University of Texas at Austin: $18,850