PYTHON - Perfectionnement Mixte : présentiel / à distance

Dernière mise à jour : 09/12/2024

Bannière visuelle de présentation de la formation
Maîtrisez les compétences avancées en Python avec cette formation de perfectionnement : développez des applications complexes, optimisez vos analyses de données, et automatisez vos processus pour répondre aux défis techniques les plus exigeants.

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Objectifs de la formation

 

LES OBJECTIFS

  • Maîtriser les techniques avancées en Python : gestion de contexte, métaclasses, closures, fonctions complexes
  • Optimiser la performance des programmes via le monitoring et le parallélisme
  • Packager et déployer des artefacts Python
  • Utiliser des bibliothèques clés pour le calcul scientifique, l'IA, le traitement XML, et la gestion réseau

Public visé

  • Ingénieurs et développeurs

Prérequis

  • Niveau : Disposer de bonnes connaissances en développement Python
    Techniques (formations en classe virtuelle) : Vous devez disposer d'un ordinateur connecté à internet, d'un micro et d'une caméra

Description


EXPLOITATION DES LIBRAIRIES CLÉS DU LANGAGE PYTHON

  • Historique et panorama de Python
  • Environnements de développement


TECHNIQUES AVANCÉES DU LANGAGE PYTHON (1/3)

  • Gestion avancée des paramètres
  • Collections simples et avancées
  • Itérateurs et générateurs avancés
  • List et dict comprehension, map/reduce et évaluation paresseuse


TECHNIQUES AVANCÉES DU LANGAGE PYTHON (2/3)

  • Gestion et définition des exceptions
  • Utilisation des context managers
  • Méthodes asynchrones
  • Typage avec type hints


TECHNIQUES AVANCÉES DU LANGAGE PYTHON (3/3)

  • Programmation orientée objets avancée
  • Propriétés, opérateurs et fonctions natives
  • Héritage multiple et algorithme MRO
  • Décorateurs, variables et méthodes de classe
  • Classes abstraites, interfaces, métaclasses et introspection


OPTIMISATION DES PERFORMANCES

  • Programmation parallèle et concurrente
  • Multi-threading, multi-processus
  • Pool de threads ou processus, objets futurs
  • Synchronisation et paradigmes de concurrence


PACKAGING ET DÉPLOIEMENT DES ARTEFACTS PYTHON

  • Installation de bibliothèques tierces
  • Gestion des dépendances du projet
  • Création de packages et environnements virtuels
  • Profiling et tests unitaires


LIBRAIRIES ESSENTIELLES (1/5) - XML ET WEB SCRAPING

  • Utilisation de XML, lxml, BeautifulSoup
  • Lecture et validation XML, chemin XPath et sélecteurs CSS
  • Transformation Python ou XSL


LIBRAIRIES ESSENTIELLES (2/5) - CALCUL SCIENTIFIQUE

  • NumPy et SciPy pour le calcul numérique
  • Tableaux multi-dimensionnels, statistiques et graphiques avec Matplotlib


LIBRAIRIES ESSENTIELLES (3/5) - TRAITEMENT DES DONNÉES

  • Pandas pour la gestion des DataFrames
  • Import/export, nettoyage, filtrage, transformation et regroupement des données


LIBRAIRIES ESSENTIELLES (4/5) - MACHINE LEARNING

  • Frameworks de ML : TensorFlow, Keras, ScikitLearn
  • Réseaux de neurones, régression, apprentissage et prédiction


LIBRAIRIES ESSENTIELLES (5/5) - FRAMEWORKS WEB/REST ET ORM

  • Django, Flask, FastAPI, SQLAlchemy
  • Création d'API REST, routage HTTP, conversion JSON, DTO pour validation des données

Modalités pédagogiques

Cette formation allie contenu théorique et exercices pratiques pour une compréhension approfondie de Python avancé. Vous découvrirez des techniques clés, comme les fonctions avancées, le parallélisme, les décorateurs, et le typage, tout en explorant l'utilisation de blocs dynamiques, context managers et la programmation orientée objets avancée pour structurer efficacement vos projets.

Les sessions pratiques vous permettront de manipuler des bibliothèques incontournables : Pandas pour la gestion de données, NumPy et SciPy pour le calcul scientifique, et les frameworks de Machine Learning comme TensorFlow, Keras et Scikit-Learn pour les réseaux de neurones et la régression.

Enfin, vous serez guidé dans la création et le déploiement de vos artefacts Python grâce aux meilleures pratiques de packaging, l'optimisation des performances et l'automatisation des workflows. L'objectif est de vous doter des bases et des outils nécessaires pour concevoir, optimiser, et déployer vos propres projets Python, qu'ils relèvent de la science des données, du développement web, ou de l'intelligence artificielle.

Moyens et supports pédagogiques

  • Exercices concrets
  • Cas pratiques
  • Quiz d'évaluation des connaissances

Modalités d'évaluation et de suivi

  • Positionnement en amont de la formation :
    • Un quiz de consolidation des pré-requis sera administré en amont de la formation
  • Suivi « pendant » :
    • Feuilles de présence
    • Exercices pratiques
    • Évaluation « fin de formation »
    • Évaluation des acquis en fin de formation
    • Formulaires d'évaluation de la formation
  • Évaluation à froid :
    • Suivi post-formation : Questionnaire de satisfaction à j+60

 

 

Compétences acquises à l'issue de la formation

  • Comprendre l'apport du Machine Learning et ses limites
  • Maîtriser les principaux algorithmes
  • Savoir créer et optimiser un modèle prédictif en python
  • Mesurer la qualité des modèles et les performances attendues en production
  • Connaître le workflow global du projet
  • Savoir mettre en oeuvre les bonnes pratiques pour éviter les écueils de ce type de projet
  • Pouvoir déployer un modèle, le superviser et le mettre à jour en production
  • Comprendre comment appliquer le Machine Learning sur des données structurées, sur du texte, et sur des séries temporelles

Matériel nécessaire à la formation

Ordinateur et/ou smartphone avec accès à internet pour se connecter à l'extranet participant

Informations sur l'accessibilité

Délais d'accès à la formation

Le délai d'accès à la formation est variable en fonction du dispositif de financement utilisé, du planning des formateurs et des contraintes du client. Pour les formations inter-entreprises, vous pouvez consulter notre calendrier en ligne ou prendre contact avec nous. Nous traitons vos demandes sous 48 heures

 

Accessibilité

Si vous êtes en situation de handicap, merci de nous en informer afin de vous accompagner, vous orienter, et étudier les compensations nécessaires pour répondre au mieux à votre demande de formation. Certaines formations peuvent nécessiter une adaptation pour les personnes en fonction de leur handicap. Nous restons disponibles pour échanger ensemble et nous pourrons vous orienter vers un de nos partenaires : Agefiph, Cap Emploi

Contact

Contactez-nous pour échanger sur vos besoins !

✉️ formation@napsia.com

📞 05 62 84 10 13

Session sélectionnée

  • 10/06/25 → 13/06/25
    Toulouse (31) -

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

 

Pour vos certifications en Anglais

 

 

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

 

Pour vos certifications en Anglais, Allemand, Espagnol, Français, Italien

 

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

 

Pour vos certifications en Anglais, Arabe, Français Langues Etrangères (FLE), Français Professionnel (FP)