Inverted CERN School of Computing 2023

Lectures and exercises

• Ahmed Abdelmotteleb (University of Warwick (GB))
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    Exercise: Quantum Computing (1/2)

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    Exercise: Quantum Computing (2/2)

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    Quantum Computing (1/2)

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    Quantum Computing (2/2)

• Martin Cejp (CERN)
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    How a real-world C++ compiler works

• Tom Dack (Science and Technology Facilities Council STFC (GB))
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    Authentication and Authorization for the WLCG

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    Exercise: Authentication and Authorization for the WLCG

• Jack Henschel (CERN)
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    Cloud & Containers - Everything you need to know

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    Exercise: Cloud & Containers - Everything you need to know (1/2)

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    Exercise: Cloud & Containers - Everything you need to know (2/2)

• Ivan Kabadzhov (Albert Ludwig University of Freiburg)
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    CPU Performance Profiling on Linux in the HEP Context

• Peter Kicsiny (EPFL)
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    Exercise: Multiplatform programming with python

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    Multiplatform Programming with Python

• Piotr Konopka (CERN)
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    Everything that can go wrong in a message passing system

• Charis Kleio Koraka (University of Wisconsin Madison (US))
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    A simple introduction to accelerated computing

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    Exercise: A simple introduction to accelerated computing

• Valeriia Lukashenko (Nikhef National institute for subatomic physics (NL))
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    The most beautiful line you can draw with Kalman filter (1/2)

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    The most beautiful line you can draw with Kalman filter (2/2)

• Michal Maciejewski
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    Exercise: MLOps - Going from Good to Great

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    MLOps - Going from Good to Great

• Alberto Pace (CERN)
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    Introduction

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    Opening welcome session

• Enrica Maria Porcari (CERN)
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    Opening welcome session

• Jacopo Talpini (Università degli Studi di Milano-Bicocca)
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    An introduction to Bayesian neural networks and uncertainty quantification in neural networks

• Ilias Tsaklidis
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    Graph Neural Networks: From fundamentals to Physics application

• Felix Wagner (HEPHY Vienna)
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    A Crash Course on Reinforcement Learning