NP-hardness

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Theory of Computation: NP Problems Examples

Examines NP problems, graph coloring, path optimization, and computational complexity distinctions in P and NP classes.

Elements of Computational Complexity

Covers quantum algorithms, complexity classes, Grover's algorithm, and quantum information in computational complexity.

Quantum Approximate Optimization Algorithm

Covers the Quantum Approximate Optimization Algorithm, physically inspired unitary coupled cluster ansatz, hardware-efficient ansatz, and variational quantum eigensolver.

Introduction to Algorithms

Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Complexity of Algorithms: Big-O Notation

Explores algorithm complexity, big-O notation, induction, recursion, and analysis of running times, covering NP problems and complexity classes.

Traveling Salesman Problem: Introduction and Approximation Methods

Introduces the Traveling Salesman Problem and explores approximation methods using Markov chains.

Theory of Computation: Decidability and Complexity

Delves into the theory of computation, covering decidability, complexity, P vs. NP, and reductions.

Introduction to Numerical Analysis

Covers the basics of numerical analysis, including adaptive feature computation, residual analysis, and the importance of well-posed problems.

Regression: High Dimensions

Explores linear regression in high dimensions and practical house price prediction from a dataset.