Event List
Handles creating, reading and updating events.
GET /api/event/?format=api&offset=20&ordering=-homepage
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Scripting languages are used on a daily basis in life science labs in order to mine huge data sets produced by high-throughput devices. This two-week course will give participants basic knowledge in python and state-of-the-art machine learning methods to analyze their own data sets.\r\nDescription:\r\nThis course is intended for PhD students, engineers and research scientists willing to acquire knowledge in scientific programming. Throughout the course, we will use Python language to lead participants from the basics of computer programming to more advanced techniques such as practical machine learning techniques.", "homepage": "https://www.pasteur.fr/fr/programmation-scientifique-python", "is_draft": false, "costs": [ "Free" ], "topics": [], "keywords": [ "Toolkit", "Tool integration", "Workflow development", "Parallelization", "Développements technologiques de l‘Information et de la Communication" ], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "being an internal personnel", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [ { "id": 12, "name": "INCEPTION", "url": "https://catalogue.france-bioinformatique.fr/api/eventsponsor/INCEPTION/?format=api" } ], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": null, "updated_at": "2024-06-10T12:40:00.372956Z", "type": "Training course", "start_date": "2017-03-26", "end_date": "2017-03-30", "venue": "", "city": "Institut Pasteur", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": "Online" }, { "id": 196, "name": "INTRODUCTION À L'ANALYSE DE DONNÉES", "shortName": "", "description": "", "homepage": "https://www.pasteur.fr/fr/introduction-data-analysis", "is_draft": false, "costs": [], "topics": [], "keywords": [], "prerequisites": [], "openTo": "Internal personnel", "accessConditions": "", "maxParticipants": null, "contacts": [], "elixirPlatforms": [], "communities": [], "sponsoredBy": [], "organisedByOrganisations": [], "organisedByTeams": [], "logo_url": "https://ressources.france-bioinformatique.fr/sites/default/files/150x150.png", "updated_at": "2022-06-02T11:50:50.627601Z", "type": "Training course", "start_date": "2019-01-13", "end_date": "2019-02-07", "venue": "", "city": "Institut Pasteur", "country": "", "geographical_range": "", "trainers": [], "trainingMaterials": [], "computingFacilities": [], "realisation_status": "past", "registration_opening": null, "registration_closing": null, "registration_status": "unknown", "courseMode": null }, { "id": 391, "name": "INTRODUCTION À L'ANALYSE DE DONNÉES", "shortName": "", "description": "\nL'utilisation de plus en plus répandue de techniques d’imagerie et de séquençage à haut-débit en biologie est en train de révolutionner les sciences du vivant et de modifier en profondeur leurs pratiques. Dans ce contexte, des outils statistiques sont développés pour permettre d’analyser ces données de hautes dimensions, et la maîtrise de ces outils devient de plus en plus nécessaire pour produire des résultats de bonne qualité. Ce cours de 4 semaines couvrira les étapes nécessaires pour mettre en place un processus d’analyse de données, depuis la planification de l’expérience jusqu’à la fouille des données en passant par l’échantillonnage, les test d’hypothèses, la modélisation statistique etc.\nCe cours s’adresse en priorité aux étudiants de première année de thèse de l’Institut Pasteur. Tout étudiant en thèse sera automatiquement inscrit à ce cours, mais les élèves de 2e année, de 3e année ou les post-doctorants peuvent également s’inscrire, dans la limite des places disponibles. Il est à noter que le cours est obligatoire pour les étudiants de 1ère année. Des dispenses partielles ou totales sont possibles pour les étudiants qui ont déjà des connaissances en statistique, en mathématique ou en physique. Le cours déroulera sur 4 semaines, 4 jours par semaine, trois heures par jour. Chaque séance de trois heures alternera cours magistral et mise en pratique. Il y aura deux sessions : la première commencera le 22 octobre 2018 et la deuxième le 14 janvier 2019.\nChacune de ces deux sessions sera précédée d’une séance d’introduction à l’informatique. Cette séance proposera des notions d’architecture de l’ordinateur, de système d’organisation des fichiers et de format de fichiers. Chaque session sera également suivie d’un cours optionnel sur l’analyse et le traitement des images.\nPour plus d’information, ainsi que pour les inscriptions au module optionnel et les demandes d’exemption, rendez-vous sur la page du cours : https://c3bi.pasteur.fr/introduction-to-data-analysis-2018-19/\nThèmes abordés\nLe module d’analyse de données couvrira un large champ de notions nécessaires aux étudiants pour planifier leurs expériences, analyser et explorer leurs données, interpréter les résultats et générer des figures à des fins de publication. Il abordera des notions de base en statistique, dont les analyses uni- et multivariées, les analyses descriptives, les distributions statistiques usuelles utilisées en biologie, ainsi que les tests d’hypothèses. Les exercices et travaux pratiques seront réalisés avec R et RStudio. 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