Pseudorandom Functions in Almost Constant Depth from Low-Noise LPN

This course covers the learning outcomes and goals of understanding Pseudorandom Functions in Almost Constant Depth from Low-Noise LPN. Students will learn about Learning Parity with Noise (LPN), the hardness of LPN, and related work. The course teaches the skills of implementing LPN-based randomized PRGs, PRFs, and LPN. The teaching method includes lectures on main results, Bernoulli Noise Extractor, Bernoulli noise sampler, and open problems. The intended audience for this course is individuals interested in cryptography, specifically in pseudorandom functions and LPN.