Dr. Maggie Myers is a lecturer for the Department of Computer Science and Division of Statistics and Scientific Computing. She currently teaches undergraduate and graduate courses in Bayesian Statistics. Her research activities range from informal learning opportunities in mathematics education to formal derivation of linear algebra algorithms. Earlier in her career she was a senior research scientist with the Charles A. Dana Center and consultant to the Southwest Educational Development Lab (SEDL).
More info: https://www.cs.utexas.edu/faculty/myers
EdX
Dive into Linear Algebra: Foundations to Frontiers, an edX course that offers a deep understanding of linear algebra principles and their application in matrix software development. This challenging yet rewarding program is ideal for mathematicians, engineers, scientists, and data professionals looking to enhance their analytical capabilities.
EdX
Discover how to systematically develop correct, loop-based programs with 'LAFF – On Programming for Correctness' on edX. Learn essential skills in formal methods to ensure your programs are reliable and produce the right output every time. Perfect for programmers seeking to enhance their ability to create error-free software.
EdX
Dive into Advanced Linear Algebra: Foundations to Frontiers (ALAFF) and elevate your understanding of linear algebra's role in computing and data science. This course will equip you with advanced knowledge, practical skills in algorithm implementation, and insights into the nuances of floating-point arithmetic.