CS-459: Foundations of probabilistic proofsProbabilistic proof systems (eg PCPs and IPs) have had a tremendous impact on theoretical computer science, as well as on real-world secure systems. They underlie delegation of computation protocols and hardness of approximation. This course covers the fou ...
CS-524: Computational complexityIn computational complexity we study the computational resources needed to solve problems and understand the relation between different types of computation.
This course advances the students knowledge of computational complexity, and develop an understa ...
CS-433: Machine learningMachine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
CS-630: Fault-tolerant quantum computingThe course explains how to execute scalable algorithms on fault-tolerant quantum computers. It describes error correction used to build reliable logical operations from noisy physical operations, and how quantum programs are mapped into logical operations ...
CS-308: Introduction to quantum computationThe course introduces the paradigm of quantum computating in an axiomatic way. We introduce the notions of quantum bits, gates, and circuits. We introduce themost important quantum algorithms. We also touch upon error-correcting codes. This course is indep ...
PHYS-541: Quantum computingThis course introduces quantum computing, starting with quantum mechanics and information theory. It covers the quantum circuit model, universal gates, foundational quantum algorithms, noise, quantum error correction, NISQ quantum algorithms, and an overvi ...
PHYS-453: Quantum electrodynamics and quantum opticsThis course develops the quantum theory of electromagnetic radiation from the principles of quantum electrodynamics. It will cover historic developments (coherent states, squeezed states, quantum theory of spontaneous emission) and moreover modern developm ...
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...
PHYS-641: Quantum ComputingAfter introducing the foundations of classical and quantum information theory, and quantum measurement, the course will address the theory and practice of digital quantum computing, covering fundamental and advanced topics such as recent quantum algorithms ...
MATH-644: Quantum AlgorithmsThe course is given by Prof. Johannes Buchmann and covers fundamental quantum algorithms and the theory behind them. It is rigorous from a mathematics, physics, and computer science perspective and requires only basic knowledge from mathematics such as cal ...
CS-602: Foundation of probabilistic proofsProbabilistic proof system (eg PCPs and IPs) have had a tremendous impact on the theoretical computer science, and have also found practical uses. They underlie delegation of computation protocols and hardness of approximation. This course covers the found ...
MATH-683: Fine-grained and parameterized complexityThe classical distinction between polynomial time solvable and NP-hard problems is often too coarse. This course covers techniques for proving more fine-grained lower and upper bounds on complexity of computational problems. ...
