Lectures related to Asymptotic computational complexity

Explores the theory of computation, undecidable problems, complexity measurement, and the P complexity class.

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Explores algorithmic complexity, visualization of functions, and algorithm efficiency analysis using Python.

Introduces the Master Theorem for analyzing algorithm time complexity through problem subdivision and formula application.

Covers the correction of an intermediate test, suggestions for the exam, and simplification techniques of poles and values.

Explores using Bernoulli de l'Hospital's theorem to compare functions' asymptotic behavior.

Explores dichotomy search algorithms, analyzing complexity and implementation details for efficient searching in sorted lists.