Analyse de données et applications dans l'industrie de la mode

Aperçu

Learn Data Analytics and Business Analysis for the Fashion Industry. Build a Smart and Data-driven Fashion Company!

What you'll learn:

How to apply data analytics in real-lifeHow data can help a fashion businessIndustry-specific application of data analytics principlesFashion analyticsProduct recommendationsConsumer-driven marketingDigital & web analyticsIntegrated demand forecastingSupply chain analytics for fashion companiesStore localization, clustering, and in-store optimizationPricing optimizationAI for uncovering fashion trendsHow to build a dashboard for a fashion company in Tableau Business analytics and AI are two of the hottest topics in the fashion industry.Not only that:

the global brands that rely on intelligent data collection and processing have a strong competitive advantage over the ones that are data blind.And this shouldn’t come as a surprise, right?We live in the 2020s.Today, in almost all industries, the most successful businesses leverage user data to extract meaningful insights and tailor their products to satisfy user wants and needs.Netflix recommends to us the movies and TV series we want to see next.Instagram knows which photos we want in our feed.So… naturally … fashion brands would want to know which clothes we want to wear, what impact the discounts have on us, and how likely it is that we’ll return after our first purchase.Top executives understand long-term gains in the fashion industry aren’t about one-off transactions. Instead, successful brands want to win us over for the long run.

The best way to do that is by employing a strategy centered around hyper-personalization. This means leveraging analytics, data science, and AI to deliver a first-rate experience that will make us a repeated customer.Pretending that current fashion trends are the same as they were a decade ago is as detrimental as operating without leveraging insights from data.

The best brands will surpass you because they will:

Price items correctlyKnow when to discount an itemRecommend the right itemsExcel at engaging customers onlineStock the right stylesBe able to choose the right colors, fabrics, and sizesSupply stores on time and efficientlyThe goal of this course is to help you learn about analytics in the fashion industry. We want to help you understand the ways in which different types of analysis can be applied in the fashion world and why that would be helpful in practice.To provide invaluable insights that correspond to the best practices in the industry, we partnered with an experienced executive who’s worked with some of the biggest brands in the industry.

His current work contract doesn’t allow us to share more info. However, his working title as Director of Data and Analytics for one of the biggest companies in the industry speaks volumes of his expertise of the topics we’ll cover together.This course is an invaluable opportunity for anyone who works in fashion or who wants to work in fashion and become a high-level executive.

Moreover, the course can also be useful to data practitioners who would like to specialize/get hired in the fashion industry. Some of the interesting topics we will cover are:

Product recommendationsConsumer-driven marketingDigital & web analyticsIntegrated demand forecastingSupply chain analytics for fashion companiesStore localization, clustering, and in-store optimizationPricing optimization, andAI for uncovering fashion trendsThis course offers tremendous upside for the time you will dedicate to it.

Not only can it be career-changing if you work in fashion, but it can also inspire you to transform your business if you’re a fashion entrepreneur who wants to succeed in the years to come.

Programme

• Introduction à l'analyse des données dans la mode
Aperçu de l'analyse des données et son importance dans la mode
Principaux types et sources de données dans l'industrie de la mode
• Méthodes de collecte de données
Comprendre les données de la mode : ventes, analyse des tendances, réseaux sociaux
Outils et techniques de collecte de données
• Traitement et nettoyage des données
Étapes de prétraitement des données
Gestion des données manquantes et des valeurs aberrantes
• Analyse exploratoire des données (EDA)
Techniques pour l'EDA
Visualisation des données de la mode
• Apprentissage automatique pour la mode
Introduction aux concepts d'apprentissage automatique
Apprentissage supervisé vs. non supervisé dans les contextes de la mode
• Analyse prédictive dans la mode
Techniques de prévision de la demande
Modèles de prédiction des tendances
• Informations client et personnalisation
Segmentation et profilage
Systèmes de recommandation dans le commerce de détail de la mode
• Applications de l'IA dans la mode
Applications de la vision par ordinateur : reconnaissance d'images et assistance au stylisme
Traitement du langage naturel pour l'analyse des tendances
• Analyse des sentiments et médias sociaux
Techniques pour l'analyse des sentiments
Mesurer l'engagement de la marque et les tendances à partir des réseaux sociaux
• Gestion des stocks et analyse de la chaîne d'approvisionnement
Optimisation des niveaux de stock avec l'analyse des données
Optimisation de la chaîne d'approvisionnement pilotée par l'IA
• Considérations éthiques et confidentialité des données
Problèmes de confidentialité dans l'analyse des données de la mode
IA éthique et ses implications dans la mode
• Études de cas et applications réelles
Histoires de succès des grandes entreprises de mode
Projets pratiques et discussions en groupe
• Tendances futures dans l'analyse des données de la mode
Technologies émergentes et leur impact potentiel
Préparation à l'avenir de l'analyse de la mode
• Revue du cours et projet final
Révision des concepts clés
Développement et présentation d'un projet final complet en analyse des données de la mode

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Enseigné par

365 Careers

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Matières

Data Science