Descriptif
Description :
Through the analysis of works pertaining to various fields, genres, and time periods, this course offers to study the ways in which French writers and artists have represented themselves throughout the centuries. Today, especially due to the omnipresence of social networks, the writing and the representation of the self have found new ways of expression. As such, they invite us to revisit some prominent literary and artistic works from the past and to wonder about potential continuities or discontinuities regarding the methods, the doubts, and the questions that guided their authors throughout the construction of their own image for posterity.
In this class, students will not only analyze and discuss all sorts of documents--paintings, photographs, literary excerpts, selfies, press articles and cartoons, scholarly articles, movies--but they will also reflect, both orally and through written assignments, on their own approach to self-representation. Consequently, active participation to class discussions is a key component of this course.
effectifs minimal / maximal:
/20Diplôme(s) concerné(s)
- Track : Large Language Models, Graphs and Applications
- MScT-Double Degree Data and Finance (DDDF)
- MScT-Internet of Things : Innovation and Management Program (IoT)
- MScT-Energy Environment : Science Technology & Management
- MScT-Data and Economics for Public Policy (DEPP)
- Titre d’Ingénieur diplômé de l’École polytechnique
- MScT-Cybersecurity (CyS)
- MScT-Economics, Data Analytics and Corporate Finance
- MScT-Environmental Engineering and Sustainability Management
- MScT-Data Science and AI for Business
- AI for Markets and Quantitative Investment (AI-MaQI)
- MScT-Visual Computing and Creative AI
- MScT-Trust and Responsible AI
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade américainPour les étudiants du diplôme AI for Markets and Quantitative Investment (AI-MaQI)
Pour les étudiants du diplôme MScT-Internet of Things : Innovation and Management Program (IoT)
Pour les étudiants du diplôme MScT-Double Degree Data and Finance (DDDF)
Pour les étudiants du diplôme MScT-Cybersecurity (CyS)
Pour les étudiants du diplôme Track : Large Language Models, Graphs and Applications
Pour les étudiants du diplôme MScT-Trust and Responsible AI
Pour les étudiants du diplôme MScT-Energy Environment : Science Technology & Management
Pour les étudiants du diplôme MScT-Environmental Engineering and Sustainability Management
Pour les étudiants du diplôme MScT-Data and Economics for Public Policy (DEPP)
Pour les étudiants du diplôme MScT-Data Science and AI for Business
Pour les étudiants du diplôme MScT-Economics, Data Analytics and Corporate Finance
Pour les étudiants du diplôme MScT-Visual Computing and Creative AI
Le rattrapage est autorisé (Max entre les deux notes)- le rattrapage est obligatoire si :
- Note initiale < 10
- le rattrapage peut être demandé par l'étudiant si :
- Note initiale < 10
- Crédits ECTS acquis : 0 ECTS
La note obtenue rentre dans le calcul de votre GPA.