i2i 2025

Liste des Contributions

1. The Unix Shell

Michel Jouvin (IJCLab)

24/03/2025 09:00

The Unix shell has been around longer than most of its users have been alive. It has survived because it’s a powerful tool that allows users to perform complex and powerful tasks, often with just a few keystrokes or lines of code. It helps users automate repetitive tasks and easily combine smaller tasks into larger, more powerful workflows.
1. Introducing the Shell
2. Navigating Files and...

2. Git Survival Guide

Michel Jouvin (IJCLab)

24/03/2025 14:00

In this survival guide, we will explore how to effectively use Git to manage and access the version history of any set of text files (code, manuscripts written in LaTeX, etc.), both in the context of team an personal projects. Specifically, we will cover the following points:
- Initializing a Git repository
- Tracking changes and managing branches
- Merging and rebasing
- Resolving...

19. Containers

Vincent Rouvreau (INRIA)

25/03/2025 09:00

This training aims to give a taste of Docker with a hands-on experience. Docker concepts and its architecture will be explained in their basics. The main objective of this training is to show a complete workflow that could be useful to everyone.

By the end of the course, participants should have a basic understanding of the concepts and some experience with the basic Docker commands that...

13. Introduction to Machine Learning

Francoise BOUVET (IJCLab - CNRS - UPsay)

25/03/2025 14:00

We will describe the main concepts of Machine Learning (ML) and give some clues to address a problem of ML. In particular, we will talk about :
- the concepts of AI/Machine Learning/Deep Learning,
- supervised/unsupervised learning,
- the preprocessing of the data,
- the general principle of the algorithm,
- the main pitfalls,
- the evaluation of the training and the outcomes.
Some...

3. Paris-Saclay Computing Center Howto

M. Guillaume PHILIPPON (IJCLab - CNRS), Dr marco leoni

26/03/2025 14:00

This course is aimed at students wishing to learn how to use the scientific computing platforms at the Paris Saclay Computing Center (https://mesocentre.universite-paris-saclay.fr/). We will review the different existing computing architectures (cloud, supercomputer). We will then look at how to access the VirtualData cloud and the Ruche HPC computer, and how to use the resources effectively...

14. Introduction to Deep Learning

Francoise BOUVET (IJCLab - CNRS - UPsay)

27/03/2025 09:00

We will describe the main concepts of Deep Learning (DL). We will focus on Multilayer Neural Network (MLP) and Convolution Neural Network (CNN).
In particular, we will talk about :
- artificial neuron,
- MLP : structure and how it works,
- CNN : structure and how it works,
- a brief review of other NN structures.
Some exercises will be provided to program simple MLP and CNN in Python...

17. GitLab Projects and Continuous Integration

Vincent Rouvreau (INRIA)

27/03/2025 14:00

This course is NOT ABOUT GIT; we will focus on using GitLab for software project management. You will learn to leverage GitLab's features to facilitate collaborative development, automate your tests, and publish code releases. Specifically, we will cover the following points:
- Creating a project in GitLab
- Managing members and permissions
- Working with issues: labels, milestones,...

10. Make Your Code More Robust 1/2

Hadrien Grasland (IJCLab), Julien Peloton (CNRS-IJCLab)

28/03/2025 09:00

Discovery of software engineering tools and methodologies to write more tested,
documented code that is easier to understand and maintain.
- static analysis
- tests
- documentation
The examples will be based on the C++ and Python programming languages.

Prerequisites: some knowledge of C++ or Python.

11. Make Your Code More Robust 2/2

Hadrien Grasland (IJCLab), Julien Peloton (CNRS-IJCLab)

28/03/2025 14:00

Second part of "Make Your Code More Robust". See the contribution "Make Your Code More Robust 1/2".

4. Python Traps & Pitfalls

David Chamont (IJCLab - IN2P3 - CNRS)

31/03/2025 09:00

First, we'll take a closer look at the basic mechanisms of the Python language, beyond what can be guessed by blindly copying and pasting examples, in order to avoid the most common traps and pitfalls. Then, we'll debate the interactions with Linux. In particular, we will talk about :
- variables semantic, duck typing,
- automatic memory management,
- builtin types and collections,
-...

5. Object-Oriented C++

Ivana Hrivnacova

31/03/2025 14:00

Get familiar with the object-oriented programming with C++. The lectures and hands-on aim to prepare students to use and/or contribute to large C++-based projects, such as Geant4.
- Introduction to object-oriented methodology
- Class definition and implementation
- Class data members and member functions/methods
- Static data members, member functions/methods
- Base class and derived...

12. CMake Survival Guide

Philip Deegan (https://www.lpp.polytechnique.fr/?lang=en)

01/04/2025 14:00

Introduction to CMake, which is the most widely used tool for managing C/C++ projects, especially in a cross platform context. The course is targeted at people who have some programming experience with C/C++ or Fortran.
In particular, we will talk about:
- building simple binaries and libraries
- build and running tests via ctest
- integrating third party applications
- modern cmake best...

6. C++17 Initiation for Pythonists

David Chamont (IJCLab - IN2P3 - CNRS)

02/04/2025 09:00

First contact with C++, in its most used version in new physics projects : aka C++17.
The course is targeted at people who have programming experience, especially with Python. In particular, we will talk about :
- builtin types, variables, functions,
- passing arguments by value and by reference,
- type inference and templates,
- returning a tuple of values,
- std::vector vs...

7. Make Your Code More Accurate

Dr Vincent LAFAGE (IJCLab)

02/04/2025 14:00

When using numbers of type float or double, are you aware that 0.1+0.2 does not equal 0.3 ? Let’s review the theory behind such pitfalls, and discuss some case studies :
- the quadratic equation in kinematics calculations
- variance calculations in data analysis
- calculations with complex numbers
- accurate summation in large Monte-Carlo calculations
- precision in matrix and geometry...

18. Data Basics

Dr Vincent LAFAGE (IJCLab)

03/04/2025 09:00

Contenu surprise...

8. Make Your Code More Efficient 1/2

Hadrien Grasland (IJCLab)

04/04/2025 09:00

Most computer programs are inefficient and could serve the same purpose while using 10-1000x less resources (time, energy, memory…). However, achieving this result requires know-how that is not part of the typical programming curriculum. In this course, you will learn a general methodology to make any program use computing resources more efficiently:
1. Safety first
2. Set a useful...

9. Make Your Code More Efficient 2/2

Hadrien Grasland (IJCLab)

04/04/2025 14:00

Second part of "Make Your Code More Efficient". See the contribution "Make Your Code More Efficient 1/2".

16. Open Code and Data

Dr Philippe Gauron (IJCLab/CNRS-Université Paris-Saclay)

Research is based on reproducibility and an incremental improvement process. Open Science movement has been developed to facilitate this work and relies on 3 legs: open access to publications, open data and libre software.
Topics :
- open data
- their organization, the conditions of their publication and their reuse
- their valorization
- Free/libre software
- the software licences,
-...