FUN

Chimiometrie, chapitre 1/2: les méthodes non supervisées (FUN)

Offered by Agreenium,
Chimiometrie, chapitre 1/2: les méthodes non supervisées (FUN)

Peut-on estimer la composition chimique d'un échantillon en quelques secondes et sans le toucher ? Identifier son origine ? Oui ! C'est possible, en réalisant l'acquisition d'un spectre de l'échantillon et son traitement avec des outils de chimiométrie.

Chemoocs est destiné à vous rendre autonome en chimiométrie. Mais le contenu est dense! C'est pourquoi le mooc a été divisé en deux chapitres. Le présent chapitre, le premier, porte sur les méthodes non supervisées. Vous aurez quelques mois pour assimiler son contenu. Ensuite, le second chapitre, pour lequel il faudra vous re-inscrire sur FUN, portera sur les méthodes supervisées et la validation de méthodes analytiques. Le teaser ci-dessus donne plus de détails sur le contenu.

Chemoocs est orienté vers les applications de spectrométrie proche infrarouge, les plus répandues. Toutefois, la chimiométrie est ouverte à d'autres domaines spectraux : moyen infrarouge, ultraviolet, visible, fluorescence ou Raman, ainsi qu'à bien d'autres applications non spectrales. Donc pourquoi pas dans votre domaine ?
Vous appliquerez vos connaissances en réalisant nos exercices d'application grâce au logiciel ChemFlow, gratuit et accessible via un simple navigateur internet depuis un ordinateur ou un smartphone. ChemFlow a été concu pour être aussi convivial et intuitif que possible. Ainsi, il ne nécessite aucune connaissance en programmation.
A la fin de ce mooc, vous aurez acquis le savoir-faire nécessaire pour traiter vos propres données.
Bienvenue dans le monde fascinant de la chimiométrie.

Plan du cours

Semaine 0 :

  • Présentation du mooc
  • Prise en main de la plateforme FUN
  • Découverte du logiciel ChemFlow
  • Introduction à la chimiométrie avec quelques définitions

Semaine 1 :

  • Statistiques simples
  • ACP (1/2)

Semaine 2 :

  • ACP (2/2)
  • Prétraitements (1/2)

Semaine 3 :

  • Classification non supervisée
  • Prétraitements (2/2)

Semaine 4 :

  • Décomposition spectrale (démélange)
  • Analyse en composantes indépendantes
  • Données N-way: méthode PARAFAC

Semaine 5 :

  • Données multiblocs: introduction
  • Méthode multiblocs, méthode ACOM

Semaine 6 :

  • Méthode multiblocs, méthode ACCPS
  • Méthode multiblocs, méthode STATIS
Go to Class
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