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.)
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
- 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
Advanced Monte Carlo Methods
- Variance reduction in Monte Carlo simulations
- Techniques: importance sampling, Russian roulette, splitting
- Applications in reactor physics and shielding
- Time-dependence, parallelization, and cost-accuracy trade-offs
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
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
Databases
- Database Architectures - past, present, future
- Reliability and Scalability of Databases
- Vector Databases & AI Workloads
Additional lectures
Student lightning talks session
