Detailed educational programme for the first year of the Paris-Saclay CPES

This mathematics course focuses on three main areas: algebra, analysis, and probability, and is based on the curriculum of scientific preparatory classes.

It aims to strengthen high school fundamentals while introducing new concepts such as vector spaces, linear applications, numerical series, and probability on a finite set.

This course covers the basics of programming in Python, with an approach focused on functional programming, algorithms, and data structures (lists, trees, graphs).

It includes formal logic, as well as databases and formal languages (automata, regular expressions).

Students also learn validation, testing, recursion, and proofs by induction.

This biology course is based on the first-year curriculum of the BCPST preparatory classes.

It focuses on the study of living organisms at several levels: molecular, cellular, organism, and ecosystem. It also covers cell organization, metabolism (respiration, nutrition), as well as genetics (structure of DNA, transmission of genetic information).

This course is based on the curriculum of the B/L preparatory classes and provides advanced training dedicated to the scientific analysis of contemporary societies.

It covers major topics such as the production and dynamics of social order (individuals, socialization, norms, deviance), social relations and stratification (class, gender, age, social mobility), cultures and their diversity, as well as power, political participation, and collective action. This program aims to convey the key concepts of sociology while developing students' analytical rigor and argumentation skills.

This module offers a structured overview of the major fields of economics, combining historical, theoretical, and applied approaches.

Students explore the foundations of economic thought, the history and evolution of the international financial system, as well as macroeconomic and microeconomic analysis tools.

This course introduces students to the fundamental methods of statistical analysis and data processing in Python.

The practical sessions use the most widely used numerical libraries (numpy, pandas, scikit-learn) and include a paired project applied to real datasets. The most advanced students can experiment with implementing simplified deep learning models.

This module combines statistical rigor, scientific programming practice, and the use of modern machine learning tools.

The introductory AI course offers a playful and visual initiation to artificial intelligence - more specifically to statistical learning - through robot control.

The aim, based on practical work, is to develop intuition about learning algorithms (supervised, unsupervised, reinforcement), gradually leading to mathematical formulations.

Implementation will provide opportunities to work with neural networks, computer vision, and language processing. The necessary basics of Python programming will be introduced along the way.

This introductory data science course presents the basics of data collection, processing, analysis, and visualization (including image analysis).

It covers the fundamentals of descriptive statistics and probability theory, using Python.

Through an image analysis project, students learn to follow the complete workflow of a data project, from defining the problem to communicating results, with a strong practical component.

The introductory statistics course presents the fundamental concepts of descriptive and inferential statistics, enabling the collection, organization, analysis, and interpretation of numerical data.

It introduces students to the main methods for summarizing data, evaluating relationships between variables, and performing estimations and hypothesis tests.

This course takes an action-oriented approach to the five skills (listening and reading comprehension, written expression, continuous and interactive oral expression), with work on the pronunciation of vowel sounds.

Interaction takes place through written and/or audiovisual documents focused on environmental and sustainable development issues, and a communication scenario as part of a year-long project. Intercultural communication may also be addressed within the framework of the project.

Physical, sports, and artistic activities chosen by the student or language instruction.

The SPOC Critical Thinking / Science in Society is an online course designed to raise students' awareness of the issues involved in the interactions between science and society by developing their critical thinking skills.

It consists of five sessions of engaging exercises using audio, video, and textual resources. Each session is linked to a theme covering a specific field of scientific knowledge, and to a question exploring a specific aspect of the interactions between science and society.

The Solidarity Project is listed in the Year 1 summary table with 20h and 0 ECTS.