[{"command":"insert","method":null,"selector":".course-modal-ajax-placeholder-956200","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  Quantum Machine Learning\n\u003C\/h2\u003E\n                  \u003Cdiv class=\u0022field-spacing\u0022\u003E\n        \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EECTS :\n          2.5\n        \u003C\/div\u003E\n      \u003C\/div\u003E\n                  \u003Cdiv class=\u0022field-spacing\u0022\u003E\n        \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ESemestre calendaire :\n          Semester 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\u003ECours magistraux :\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\u003ETravaux dirig\u00e9s :\u003C\/span\u003E\n                                      \u003Cspan\u003E12\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\u003EKnowledge of quantum circuit programming is assumed, including Variational Quantum Algorithm. Knowledge of classical ML will be useful, but reminders will be given at the beginning of courses that require it.\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 course presents the main concepts and algorithms of quantum ML based on quantum circuits for digital architectures and introduces some methods of quantum ML algorithms on analog architectures. Firstly, the course introduces embedding techniques in Hilbert space and some mechanisms for computing gradients or alternative solutions. Based on these mechanisms, the course presents various quantum algorithms for data clustering, neural networks and generative networks. Built around variational quantum algorithms and quantum circuits, they can run on digital current NISQ or future FTQC architectures to perform classifications or predictions. Finally, the course introduces some quantum algorithms mainly designed for analog quantum architectures: QUBO optimization methods used to train some ML models and quantum reservoir algorithms. Several tutorials and labs on digital or analog quantum development environments, with and without noise, and a few experiments on real QPUs, will fill the course.\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003ECourse outline\u003C\/strong\u003E \u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003EPart I: Principles and basic mechanisms\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E1. From ML to Quantum ML\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E2. Quantum embedding methods\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E3. Quantum gradient computing methods \u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003EPart II: QML based on VQA and quantum circuits\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E4. Quantum data clustering\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E5. Quantum Neural Networks\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E6. Quantum generator networks\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E7. Parallel circuits of neural networks \u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003EPart III: QML on analog quantum architectures\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E8. QUBO method for ML\u0026nbsp;\u003C\/p\u003E\n\u003Cp\u003E9. Quantum reservoirs\u003C\/p\u003E\n\u003Cp\u003ESome lessons include reminders of classic ML at the beginning\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\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}]