CERN School of Computing 2019

Classes per lecturer

• Francois Fluckiger
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    Networking Fundamentals L1: Transport Network: The essentials

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    Networking Fundamentals L2: Focus on End-Systems

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    Special evening talk: When Internet history meets philosophy

• Andrei Gheata (CERN)
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    Software Design L2: Base Concepts of Parallel Programming: A Pragmatic Approach

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    Software Design L3: Understanding, Debugging and Profiling a Complex Multithreaded Application

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    Software Design E1

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    Software Design E2

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    Software Design E3

• Bob Jacobsen (UC Berkeley)
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    Data Science: Tools for interactive exploration

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    Tools and Techniques L1: Introduction

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    Tools and Techniques L2: Tools for Collaboration, Software Engineering Across the Project

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    Tools and Techniques E1

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    Tools and Techniques E2

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    Tools and Techniques E3

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    Tools and Techniques E4

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    Tools and Techniques E5

• Cosmin Lazar (Bosch)
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    Guest talk: Industrial applications of data science

• Sebastian Lopienski (CERN)
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    Software Security L1: Introduction

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    Software Security L2: Security in different phases of software development

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    Software Security E1

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    Software Security E2

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    Software Security E3

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    Software Security L3: Web application security, exercise debriefing

• Eamonn Maguire
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    Data Visualization L1: The Theory Behind Data Visualization

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    Data Visualization L2: Practical Applications of Theory and Multi-Dimensional Data Visualization

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    Data Visualization E1

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    Data Visualization E2

• Virginia Niculescu ("Babes-Bolyai" University)
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    Guest talk: Using MPI and OpenMP in building High Performance Applications

• Alberto Pace (CERN)
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    Data Technologies L1: Setting the scene: Storage technologies, Storage reliability

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    Data Technologies L2: Cryptography, authentication authorization and accounting 1 (PKI)

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    Data Technologies L3: Cryptography, authentication authorization and accounting 2 (Kerberos, OAuth, OpenID)

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    Data Technologies L4: Distributed Hash Tables, Data Replication, Caching, Monitoring, Alarms and Quota 1

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    Data Technologies L5: Distributed Hash Tables, Data Replication, Caching, Monitoring, Alarms and Quota 2

• Andreas Peters (CERN)
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    Data Technologies E1

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    Data Technologies E2

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    Data Technologies E3

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    Data Technologies E4

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    Data Technologies L1: Introduction

• Ivica Puljak (University of Split)
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    Data Analysis L1: Introduction to data analysis and Monte Carlo method

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    Data Analysis L2: Distributions and estimators

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    Data Analysis L3: Confidence intervals

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    Data Analysis L4: Statistical tests

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    Data Analysis E1: Monte Carlo method and Fitting with Root

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    Data Analysis E2: Confidence interval

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    Data Analysis E3: Hypothesis testing

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    Special evening talk: Future of the Universe and of Humanity

• Arnulf Quadt (University of Göttingen)
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    Introduction to Physics Computing L1: Hadron Collider Physics

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    Introduction to Physics Computing L2: Digital Data, Simulation and Reconstruction in Modern Particle Physics Experiments

• Anna Scaife (University of Manchester)
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    Machine Learning L1: Understanding Classification

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    Machine Learning L2: Gaussian Process Modelling

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    Machine Learning L3: Convolutional Neural Networks

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    Machine Learning E1

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    Machine Learning E2

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    Machine Learning E3

• Emil Slusanschi
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    Guest lecture: Computational Science - The Third Pillar of Science?

• Enric Tejedor (CERN)
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    Software Design L1: Parallelism in a Modern HEP Data Processing Framework

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    Software Design L4: Patterns for Parallel Software Development

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    Software Design E1

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    Software Design E2

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    Software Design E3

• Liliana Teodorescu (Brunel University (GB))
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    Guest lecture: Physics-inspired computer algorithms