Stuck in Tutorial Hell? Learn Backend Dev the Right Way
Python, Prompt Engineering, Data Science — Build the Skills Employers Want Now
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore a groundbreaking lecture on coding theory presented by Dana Moshkovitz from the University of Texas at Austin. Delve into the construction of asymptotically good error-correcting codes that can be deterministically encoded in almost linear time and sub-linear space. Discover innovative techniques for creating codes that can be deterministically decoded with similar complexity. Learn about the use of hashing in encodable codes and the application of locally correctable codes combined with a novel efficient derandomization method for decodable codes. Gain insights into this cutting-edge research, which is based on joint work with Joshua Cook from the University of Texas at Austin, as part of the "Advances in the Theory of Error-Correcting Codes" series at the Simons Institute.
Syllabus
Coding Theory in Almost Linear Time and Sublinear Space
Taught by
Simons Institute