[{"command":"insert","method":null,"selector":".course-modal-ajax-placeholder-963996","data":"\u003Cdiv class=\u0022container content-rte\u0022\u003E\n  \u003Cdiv class=\u0022row\u0022\u003E\n    \u003Cdiv class=\u0022box col-md-6 bg-primary text-white\u0022\u003E\n      \u003Ch2 class=\u0022h1 text-left\u0022\u003E  AI meets IA (infectious agents): accelerating research with critical thinking\n\u003C\/h2\u003E\n                  \u003Cdiv class=\u0022field-spacing\u0022\u003E\n        \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EECTS :\n          3\n        \u003C\/div\u003E\n      \u003C\/div\u003E\n                  \u003Cdiv class=\u0022field-spacing\u0022\u003E\n        \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ESemester:\n          Semestre 1\n        \u003C\/div\u003E\n      \u003C\/div\u003E\n            \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ED\u00e9tail du volume horaire\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                          \u003Cspan class=\u0022field__label h4 mt-5 \u0022\u003ELecture:\u003C\/span\u003E\n                                      \u003Cspan\u003E6\u003C\/span\u003E\n                      \u003C\/div\u003E\n                                              \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                          \u003Cspan class=\u0022field__label h4 mt-5 \u0022\u003EDirected study:\u003C\/span\u003E\n                                      \u003Cspan\u003E12\u003C\/span\u003E\n                      \u003C\/div\u003E\n                                \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                          \u003Cspan class=\u0022field__label h4 mt-5 \u0022\u003ETutored project\u003C\/span\u003E\n                                      \u003Cspan\u003E9\u003C\/span\u003E\n                      \u003C\/div\u003E\n                                              \u003C\/div\u003E\n        \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ELangue d\u0026#039;enseignement\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003EAnglais\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n        \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EEnseignement \u00e0 distance\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003Enon\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n      \u003C\/div\u003E\n    \u003Cdiv class=\u0022box col-md-6\u0022\u003E\n            \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EPr\u00e9requis\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003E\u003Cp\u003EStudents should have a solid foundation in molecular and cellular biology, microbiology, or related biomedical sciences. Familiarity with basic data analysis or biostatistics concepts is advantageous but not mandatory. No prior programming experience is required; emphasis will be placed on conceptual understanding and interpretation of AI-based research in a biological context.\u003C\/p\u003E\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n        \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EProgramme \/ plan \/ contenus\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003E\u003Cp\u003EThis teaching unit introduces students to the interdisciplinary interface between artificial intelligence (AI) and infectious disease research. It explores how AI and machine learning approaches are transforming our understanding of pathogen biology, host\u2013pathogen interactions, and epidemiological dynamics. Students will examine how computational tools are applied to areas such as genomic analysis, diagnostics, drug discovery, and outbreak prediction.\u003C\/p\u003E\n\u003Cp\u003EThe course begins with a seminar providing an overview of the main AI tools and concepts relevant to biological and biomedical research, designed to ensure a common foundation among participants. Building on this introduction, students will undertake an applied analytical project, either individually or in small groups, using AI-based approaches to analyze scientific literature or experimental datasets. Projects will be tutored by experts in virology, microbiology, or computational science, allowing students to receive personalized guidance throughout their work.\u003C\/p\u003E\n\u003Cp\u003EThe course emphasizes critical thinking and scientific rigor rather than technical coding skills. Students will learn to assess the potential and limitations of AI methods, interpret outcomes in a biological context, and evaluate the reliability and ethical implications of data-driven research. Through lectures, interactive discussions, and analysis of real-world case studies, students will develop an informed and critical perspective on how AI contributes to infectious disease research and public health.\u003C\/p\u003E\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n        \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EObjectifs d\u0026#039;apprentissage\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003E\u003Cp\u003EBy the end of this teaching unit, students will be able to:\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ELO1.\u003C\/strong\u003E Understand and apply the fundamental principles of artificial intelligence (AI) and\/or machine learning relevant\u0026nbsp;to the study of infectious agents, including their use in diagnostics, epidemiological modeling, genomics, and drug discovery.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ELO2.\u003C\/strong\u003E Use AI-based tools and approaches to retrieve, organize, and analyze scientific literature and\/or experimental datasets, deriving meaningful biological insights from complex information.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ELO3.\u003C\/strong\u003E Evaluate and discuss case studies illustrating how AI contributes to understanding pathogen biology through the analysis of biological and biomedical data, identifying methodological gaps, and proposing reasoned strategies for improvement or alternative approaches.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ELO4.\u003C\/strong\u003E\u0026nbsp;Develop critical thinking and problem-solving skills by assessing\u0026nbsp;the robustness, reproducibility, and limitations of AI-generated results in the context of infectious disease research and\/or public health, including potential biases and ethical considerations.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ELO5.\u003C\/strong\u003E Communicate analytical outcomes effectively through written reports and oral presentations that demonstrate both methodological understanding and critical reflection on the role of AI in studying infectious agents.\u003C\/p\u003E\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n        \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EOrganisation g\u00e9n\u00e9rale et modalit\u00e9s p\u00e9dagogiques\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003E\u003Cp\u003EThe unit combines lectures by experts in virology, microbiology, and computational science with guided discussions and group work. Core sessions introduce fundamental AI concepts and their applications to infectious agents. Case studies will illustrate concrete examples of how AI is used in viral genomics, epidemiological modeling, and therapeutic design.\u003C\/p\u003E\n\u003Cp\u003EStudents will participate in critical analyses of selected scientific papers, individually or in small groups, and will present their evaluations in short oral discussions. Emphasis is placed on analytical reasoning, synthesis of interdisciplinary knowledge, and clear communication of scientific arguments.\u003C\/p\u003E\n\u003Cp\u003ECourses and conferences by experts, round tables and\/or \u201cmini conferences\u201d prepared by the students themselves.\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EAssessment methods\u003C\/strong\u003E (MCC): continuous assessment (CA) and Final oral exam (oral presentation and Q\/A). Student performance will be evaluated through a combination of active participation, an applied analytical project, and an oral presentation.\u003C\/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cstrong\u003EParticipation (15%)\u003C\/strong\u003E \u2013 Engagement in lectures, discussions, and hands-on sessions involving the use of AI tools for data or literature analysis.\u003C\/li\u003E\n\u003Cli\u003E\u003Cstrong\u003EApplied Project (45%)\u003C\/strong\u003E \u2013 Individual or group assignment in which students use AI-based methods to analyze either a selected body of scientific literature or a relevant experimental dataset. The project output in the form of a short written report will allow to assess the student\u2019s ability to select appropriate tools, interpret outputs critically, and relate findings to biological questions.\u003C\/li\u003E\n\u003Cli\u003E\u003Cstrong\u003EOral Presentation (40%)\u003C\/strong\u003E \u2013 Presentation of the project outcomes, highlighting analytical approaches, key results, limitations, and possible extensions or improvements.\u003C\/li\u003E\n\u003C\/ul\u003E\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n                                \u003Cdiv class=\u0022field-spacing\u0022\u003E\n      \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ENature de l\u0026#039;\u00e9valuation\u003C\/div\u003E\n                        \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n                                      \u003Cspan\u003EEvaluation Continue non Int\u00e9grale\u003C\/span\u003E\n                      \u003C\/div\u003E\n                  \u003C\/div\u003E\n      \u003C\/div\u003E\n  \u003C\/div\u003E\n\u003C\/div\u003E\n","settings":null}]