Lectures related to Algorithmes: introduction

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Explores algorithm complexity, analyzing efficiency and worst-case scenarios of sorting algorithms.

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

Explores communication complexity and quantum computation models in Distributed Quantum Computing.

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.