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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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Don't let this gap widen
Sans maîtrise de SciPy pour l'analyse et le calcul scientifique en Python, vos projets data stagnent dans l'inefficacité et les approximations grossières.
Une équipe perd en moyenne 30% de productivité, soit 200 heures facturables par mois gaspillées en algorithmes sous-optimaux et calculs redondants.
45% des incidents d'analyse scientifique proviennent d'erreurs numériques non gérées, entraînant des pertes financières de 40 000 € par projet raté et exposant l'entreprise à des décisions stratégiques erronées.
Chaque trimestre sans ces compétences avancées compromet votre compétitivité et votre ascension professionnelle face à des concurrents agiles.
The Maîtriser SciPy : Analyse et Calcul Scientifique en Python training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Maîtriser SciPy : Analyse et Calcul Scientifique en Python training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Maîtriser SciPy : Analyse et Calcul Scientifique en Python training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Panorama des bibliothèques scientifiques (NumPy, Pandas, Matplotlib, SciPy). Rappels sur NumPy, installation et utilisation de SciPy, structure de la bibliothèque, découverte des sous-modules essentiels (linalg, optimize, integrate, stats, etc.). Étude de cas simple d’analyse de données scientifiques.
Calculs de base en algèbre linéaire (solve, eig, svd). Optimisation numérique (recherche d’extrema, ajustement de courbes, fonctions de coût). Statistiques avancées (lois de probabilités, tests d’hypothèses, analyse descriptive, statistiques robustes). Utilisation combinée avec Pandas et Matplotlib pour la visualisation.
Méthodes d’interpolation (splines, interpolation polynomiale). Intégration numérique (trapz, quad, dblquad). Résolution d’équations différentielles ordinaires (ODE). Applications concrètes : analyse spectrale, traitement du signal, résolution de problèmes physiques et chimiques. Projets fil rouge : mise en œuvre d’un pipeline scientifique de A à Z.
Target audience
Professionnels de la data, ingénieurs, chercheurs, développeurs Python souhaitant réaliser des analyses scientifiques avancées
Prerequisites
Avoir des bases en Python, notions de mathématiques et de calcul numérique
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