• Home
  • Education
  • Virtual Laboratories For Teaching and Research At École Polytechnique

Virtual laboratories for teaching and research at École Polytechnique

École Polytechnique is embarking on a major educational and technical transformation with the introduction of virtual laboratories using the Jupyter ecosystem. This project draws on an active community and an innovative, reproducible and sovereign infrastructure, positioning the School as a leader in the digital transformation of higher education.

Benefits for students

1. A unified digital environment accessible 24/7

Virtual labs are revolutionising access to education by creating a shared workspace: 

  • Immediate accessibility: all you need is a web browser, eliminating the need to install software on different operating systems (Linux, Mac OS, Windows).
  • Constant availability: work can be carried out from anywhere and at any time, catering to students’ changing lifestyles.
  • Technological equality: the same working environment for all students, regardless of their personal equipment.
  • Immediate usability: students can get straight to work, saving considerable time compared to traditional set-ups.

2. Multidisciplinary education of the highest standard

The infrastructure supports a bespoke educational programme that is unique within French higher education, offering a range of courses covering the following fields, which will be expanded over time.

Fundamental sciences and applied mathematics

  • APM_3X062_EP - Introduction to Python 
  • APM_41012_EP - Introduction to Numerical Analysis with Jupyter 
  • APM_51051_EP - Dynamical Systems for Multi-scale Modelling 
  • APM_50179_EP - Algorithms and Software Design Principles for Applied Mathematics in Modern C++

Engineering and Mechanics: 

  • MEC431 - Mechanics of Solids (we have not been able to find the new course title)
  • MEC_51052_EP and MEC_51053_EP - Numerical Methods in Fluid Mechanics 
  • MEC_51057_EP - Machine Learning for Climate and Energy 
  • MEC_52068_EP - Fracture Mechanics

Emerging interdisciplinary fields: 

  • BIO_52101_EP - Data Science in Biological Imaging 
  • ECO_52189_EP - Cross-disciplinary perspectives on environmental issues through the study of territories
  • APM_EP_52009 - Machine Learning for Scientific Computing

3. Interactive learning and enhanced collaboration

The platform transforms the learning experience through Jupyter interactivity: 

  • Interactive notebooks: documents combining code, equations, visualisations and narrative text that can be executed in real time.
  • Collaborative editing: simplified teamwork, even remotely, preparing students for modern collaborative professions. 
  • Teacher-student interactions: direct communication via the platform, enabling personalised support.
  • Multidisciplinary projects: synergies between the 11 departments, fostering innovative cross-disciplinary approaches.

4. Access to cutting-edge technologies and preparation for the jobs of the future

The laboratories are making professional resources more widely available: 

  • HPC (high-performance computing) infrastructure: access to 8 A100 GPUs for artificial intelligence and machine learning.
  • Reproducible workflows: adoption of best practices from modern research and industry. 
  • Entrepreneurial innovation: rapid prototyping for student projects and start-ups emerging from École Polytechnique.

Benefits for teaching staff

1. A flexible and highly available digital learning environment (DLE)

Virtual labs are radically transforming teaching practices: 

  • Direct connection to Moodle: simplified management of classes and user permissions. 
  • Creation of bespoke environments: rapid development of specific environments with the dependencies required for each course. 
  • Guaranteed high availability: dedicated teaching infrastructure with 24/7 service, exceeding the ‘best effort’ principle.
  • Enhanced communication and interaction: a dedicated space enabling exchanges between teachers and students via the platform.

2. Tools for assessing and analysing learning data

The platform offers revolutionary analytical capabilities for teaching: 

  • Valuable learning data: analysis of class progress and identification of individual gaps. 
  • Educational research: development of research activities in IHL (Information Environments for Human Learning). 
  • Innovative teaching methods: experimentation with the ‘flipped classroom’ and other active approaches.
  • Data sovereignty: an alternative to proprietary solutions from large corporations (Google, Microsoft).

3. Innovative learning pathways and resource sharing

The School is developing a collaborative approach to content creation: 

  • Collaboration with the Teaching and Learning Centre: combining technical and pedagogical expertise.
  • Personalised learning pathways: enabling students to follow their own path using the available resources. 
  • Interdisciplinary sharing: reuse and adaptation of resources across the 11 departments.
  • Dedicated promotional website: showcasing the diversity and quality of the School’s teaching.

4. Reproducible workflows and open science

The infrastructure meets modern requirements for scientific transparency: 

  • Simplified publication: conversion of notebooks into scientific articles, e-books or course materials. 
  • Guaranteed reproducibility: standardised environments enabling the validation of research results.
  • Open science: alignment with UNESCO and CNRS principles for free and open-access resources.
  • Open-source development: contribution to community tools and sharing of expertise. 

Contributions to innovation

1. Democratising access to high-performance computing (HPC) technologies

Virtual laboratories remove the traditional barriers to advanced technologies: 

  • Shared HPC infrastructure: shared access to high-performance computing resources without the need for individual investment.
  • 8 A100 GPUs: democratising artificial intelligence and machine learning for all students.
  • Professional environments: the same standards as leading companies (Bloomberg stock market analysis, Netflix collaborative environment, NASA research).
  • Economic sovereignty: total control over data and infrastructure, guaranteeing security and confidentiality.

2. Accelerating the “idea-to-prototype” cycle

The platform radically transforms innovation processes: 

  • Pre-configured environments: eliminates installation and configuration time, allowing you to focus on innovation.
  • Integrated scientific libraries: immediate access to cutting-edge tools for rapid prototyping. 
  • Real-time collaboration: distributed teams working simultaneously, accelerating development cycles. 
  • Reproducible workflows: ensuring the traceability and reproducibility of the innovations developed.

3. A catalyst for interdisciplinary innovation

The convergence of the 11 departments generates unprecedented synergies: 

  • Mathematics × Biology × Computer Science × Mechanical Engineering: cross-disciplinary projects that would be impossible within traditional silos. 
  • Applied research: a seamless transition between teaching and innovative research projects. 
  • Student entrepreneurship: technical support for start-ups emerging from the School, from the initial idea to proof of concept.

4. Positioning as a global leader in educational innovation

École Polytechnique is becoming a key player in educational transformation: 

  • A replicable model: comprehensive documentation enabling other institutions to follow the same approach. 
  • Community leadership: active contribution to open-source developments and international standards. 
  • Global reach: attracting global talent through an exceptional technological infrastructure. 
  • Technology dissemination: sharing advances with the industrial sector and the international academic network.

Impact on the development of the Jupyter ecosystem

1. Technical innovation and the development of specialised extensions

The project is pushing the technological boundaries of the Jupyter ecosystem: 

  • Automated assessment tools: improvements to nbgrader (a tool that facilitates the creation and marking of assignments) and the development of new solutions for assessing exercises.
  • Advanced educational widgets: specialised extensions meeting the specific needs of teaching. 
  • Optimised Moodle integration: robust solutions for user rights management and interoperability. 
  • HPC/GPU interface: development of tools for transparent access to high-performance computing resources. 

2. Reference model for institutional adoption

École Polytechnique develops and documents best practices: 

  • Reproducible documentation: full publication of the deployment process to facilitate adoption by other institutions.
  • Reference architecture: a proven technical model for large-scale academic deployments. 
  • Sovereignty strategy: a partnership framework striking a balance between private cloud (VirtualData/Paris-Saclay) and commercial cloud (OVH). 
  • Optimised resource management: solutions for the efficient allocation of capacity across multiple users.

This project is transforming École Polytechnique into a global catalyst for digital educational innovation. Drawing on the in-house technical expertise developed over several years and strategic partnerships, the School is positioning itself as a leader in educational transformation within higher education.

The infrastructure developed addresses the following challenges simultaneously: 

  • Accessibility: democratising access to cutting-edge technologies. 
  • Excellence: maintaining the École’s high academic standards.
  • Innovation: actively contributing to the global technological ecosystem. 
  • Sovereignty: data control and technological independence.

This project perfectly illustrates the vision of an open, collaborative and innovative École Polytechnique for the 21st century, capable of training future scientific and technological leaders in a digital environment of excellence.