Program Overview

Introduction to the Machine Learning for Scientific Discovery Program

The École normale supérieure (ENS) has introduced a new course in artificial intelligence (AI) called Machine Learning for Scientific Discovery: From Foundations to Applications. This course is designed for students from various scientific departments and aims to provide them with a solid foundation in machine learning and its applications in scientific research.

Course Overview

The course is taught by Tony Bonnaire, a researcher at the CNRS, and Marc Lelarge, a professor at the ENS-PSL and a researcher at the INRIA. It consists of a common core of eight weeks, which presents the foundations of machine learning and its scientific applications. The course also includes a research project, which is supervised by researchers from different departments and allows students to apply the concepts learned in the course to real-world problems.

Course Objectives

The objective of the course is to provide students with a solid understanding of machine learning and its applications in scientific research. The course covers the foundations of machine learning, including statistical models and deep learning approaches, and their applications in various scientific fields. The course also aims to equip students with the skills and knowledge necessary to apply machine learning techniques to their own research problems.

Prerequisites

To enroll in the course, students are required to have a good understanding of the Python programming language, differential calculus, linear algebra, and basic probability and statistics.

Course Content

The course introduces students to the foundations of machine learning, including:

• Statistical models
• Deep learning approaches
• Applications of machine learning in scientific research The course also includes a research project, which allows students to apply the concepts learned in the course to real-world problems.

Research Areas

The course covers various research areas, including:

• Biology
• Physics
• Geosciences
• Sciences cognitives
• Social sciences

Why ENS for AI Research and Education

The ENS is a leading institution for research and education in AI, offering a unique environment for students to learn from and collaborate with top researchers in the field. The ENS benefits from an teaching anchored in research, with courses taught by active researchers in their domains, and students are exposed early to the scientific approach. The ENS is one of the rare places where the best students in AI can collaborate directly with the best in biology, physics, or cognitive sciences, and vice versa.

The Future of AI in Scientific Research

The integration of AI in scientific research is expected to accelerate the discovery process, allowing researchers to explore larger solution spaces, automate certain analysis steps, and generate new hypotheses. The ENS aims to equip students with the skills and knowledge necessary to use AI autonomously in their research, enabling them to take a problem from their domain, formulate it as a machine learning problem, and apply the appropriate methods to obtain scientific results.