1. Basic Quantum Computing Algorithms and Their Implementation in Cirq, 5-6 Sept 2023 online:

Quantum computers are based on a completely different principle than classical computers. This course aims to explain this difference by showing how basic quantum computing algorithms work in practice. It is focused on the theoretical foundations, mathematical description and practical testing of the resulting quantum circuits.

On the first day, a brief introduction to quantum computing explanation of quantum entanglement and its applications (e.g., quantum teleportation) will be made. Then the principle of quantum superposition will be clarified, and it will be shown on Bernstein-Vazirani and Simon’s algorithms how this superposition can be used in practice.

The second day will be started with Grover’s algorithm and then switch to the quantum Fourier transform and practical examples of its use (quantum phase estimation, Shor’s algorithm).

By the end of this course, participants should understand why quantum computers are able to solve the problem of exponential complexity in less than exponential time, what the difference is between natural quantum parallelism and parallel programming on HPC, or what the principle of quantum teleportation is based on. Furthermore, thanks to the hands-on part, they should be able to program and run a simple quantum circuit in the Cirq environment.

Level: beginner, intermediate

Language: English

Prerequisites

Basic knowledge of linear algebra, complex numbers, and programming in Python.

For further information and registration, please visit the following link

2.Transformers: From Building Blocks to Real-World Applications, 11-13 Sept 2023 online:

In this course, participants learn the building blocks of transformer architectures to apply them to their projects. These novel methods will be differentiated against existing methods, showing their advantages and disadvantages. Different hands-on exercises give the participants room to explore how the transformers work in various fields of application.

Language of instruction: English

Level: Intermediate

Prerequisites: Basic knowledge of Python. Knowledge of PyTorch is helpful but not mandatory. Basic principles of deep learning and machine learning.

For further information and registration, please visit the following link