8–21 Sept 2024
DESY
Europe/Zurich timezone

Academic programme

Academic Programme

 
 

The complete programme will offer over 50 hours of lectures and hands-on exercises. The programme is organized over three distinct tracks: Physics Computing, Software Engineering, and Data Technologies. In addition, guest lectures, student presentations and special evening talks will be organised.

(Please note that this programme may be subject to minor changes.)


The final programme and lecture timetable will be released soon.

 

  • Physics Computing

    Introduction to Physics Computing

    • foundations of particle physics
    • introduction to the Standard Model
    • event filtering
    • calibration and alignment
    • event reconstruction
    • event simulation
    • physics analysis
    • data flow and computing resources

    Data Science and Interactive Data Exploration

    • introduction, data science tools
    • using data from different sources
    • non-numeric data

    Data Analysis

    • introduction to data analysis
    • probability density functions and Monte Carlo methods
    • parameter estimation and confidence intervals
    • hypothesis testing and p-value

     

    Introduction to Machine Learning

    • what is machine learning
    • learning algorithm, loss function, optimisation
    • overfitting and underfitting
    • machine learning in HEP

  • Software Engineering

    Tools and Techniques

    • introduction to software engineering
    • test frameworks, memory checkers
    • collaborating on complex software

     

    Software Design in the Many-Cores Era

    • Amdahl's and Gustafson's laws, data and task parallelism
    • parallel programming in C++, concurrency and synchronisation
    • performance and correctness - profiling and debugging multithreaded applications
    • patterns for parallel software development

     

    Creating Secure Software

    • introduction to computer security
    • security in different phases of software development
    • web application security

     

    Sustainable computing

     

  • Data Technologies

    Data Management

    • data workflow, storage models and technologies
    • reliability and error correction
    • practical cryptography: hash functions, symmetric and asymmetric encryption, digital signatures
    • authentication, authorization and accounting: PKI, certificates, Kerberos, OpenID, OAuth etc.
    • distributed hash tables, block storage, data replication, caching

     

    Data and Storage Technologies

    • storage technologies: present and future
    • data formats and access patterns
    • optimizations in IO systems
    • redundancy, cloud storage

     

  • Additional lectures

    Student lightning talks session