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06/01/2020 - In response to high demand for professionals with scientific and technical training to understand and work with massive amounts of data, The University of Texas at Austin is set to launch a new online master’s degree program in data science. Pending final approval by UT System and the Texas Higher Education Coordinating Board, the new program will be a collaboration between the Department of Computer Science, ranked among the top 10 programs in the country by U.S.

05/10/2019 - Is my code fast? Can it be faster? Scientific computing, machine learning, and data science are about solving problems that are compute intensive. Choosing the right algorithm, extracting parallelism at various levels, and amortizing the cost of data movement are vital to achieving scalable speedup and high performance.

10/09/2018 - The University of Texas at Austin is making plans to bring its top-ranked computer science graduate program to students and professionals beyond campus through a new online master’s degree program.

05/15/2018 - The only effective way to raise the confidence level of a program significantly is to give a convincing proof of its correctness. But one should not first make the program and then prove its correctness, because then the requirement of providing the proof would only increase the poor programmer’s burden. On the contrary: the programmer should let correctness proof and program grow hand-in-hand. - “The Humble Programmer,” Edsger W. Dijkstra (1972)

01/22/2018 - On January 23, 2018, UTCS faculty (and spouses) Robert van de Geijn and Maggie Myers will kick off the seventh run of their 16 week MOOCs (Massively Open Online Course) on linear algebra from a computer science perspective called Linear Algebra - Foundations to Frontiers (LAFF). The course is self-paced with a suggested calendar but everything is due by the close of the course on May 31.

06/27/2014 - On January 29, UT Computer Science made its first venture into the world of MOOCs (massively open online courses). Learn linear algebra theory with the practice of software library development.