Uranie training sessions
The developpement team of the Uranie platform proposes on a regular basis some training sessions in order to help handling the methods provided along with the platform, but also some more dedicated sessions, focused on specific issues, such as sensitivity analysis, surrogate models generation, optimisation, calibration, introduction to AI technics. Don't hesitate to contact us for more details on these.Handling the Uranie platform
Few times a year, the Uranie team is organising training sessions to help handle both methods and their interfaces, these sessions being done on several sites. The prerequesites to attend these are the following:- Knowledge of either C++ or Python
- Basic knowledge of Linux operating system
- Basic knowledge of statistic
Each training session is in general organised over a three-day period, the programm being displayed below. The next planned session is not yet planned but will follow the programm shown below.
First day
- Welcome
- Morning
- General introduction to ROOT and Uranie
- First usage of ROOT and Jupyter
- Afternoon
- Dataserver module
- Hands-on
Second day
- Welcome
- Morning
- Sampler module: the design-of-experiments
- Launcher module: launching codes
- Hands-on
- Afternoon
- Optimizer module: optimising issues
- Hands-on
Third day
- Welcome
- Morning
- Sensitivity module: sensitivity analysis
- Hands-on
- Afternoon
- Modeler module: surrogate models introduction
- Hands-on
- Open discussions
Dedicated trainings
The dedicated training sessions are less regular than the previous ones and their aim is to get deeper both in the methodological aspect of each and every subjet and in their implementation as done in Uranie (many methods being glossed over in the first level of traininf introduced above). These sessions can shed a light on sensitivity analysis, surrogate model generation, optimisation, calibration, AI technics. During these sessions, on top of getting deeper in the subjets, the trainees can bring along their own cases so that specificities can be discussed with the development team. Don't hesitate to contact us for further details.
- General introduction to ROOT and Uranie
- First usage of ROOT and Jupyter
- Dataserver module
- Hands-on
- Welcome
- Morning
- Sampler module: the design-of-experiments
- Launcher module: launching codes
- Hands-on
- Afternoon
- Optimizer module: optimising issues
- Hands-on
Third day
- Welcome
- Morning
- Sensitivity module: sensitivity analysis
- Hands-on
- Afternoon
- Modeler module: surrogate models introduction
- Hands-on
- Open discussions
Dedicated trainings
The dedicated training sessions are less regular than the previous ones and their aim is to get deeper both in the methodological aspect of each and every subjet and in their implementation as done in Uranie (many methods being glossed over in the first level of traininf introduced above). These sessions can shed a light on sensitivity analysis, surrogate model generation, optimisation, calibration, AI technics. During these sessions, on top of getting deeper in the subjets, the trainees can bring along their own cases so that specificities can be discussed with the development team. Don't hesitate to contact us for further details.
- Sensitivity module: sensitivity analysis
- Hands-on
- Modeler module: surrogate models introduction
- Hands-on
- Open discussions