Analítica de Datos y Aplicaciones en la Industria de la Moda

Resumen

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.

Programa

• Introducción al Análisis de Datos en la Moda
Panorama del análisis de datos y su importancia en la moda
Tipos y fuentes clave de datos en la industria de la moda
• Métodos de Recolección de Datos
Entendiendo los datos de moda: ventas, análisis de tendencias, redes sociales
Herramientas y técnicas para la recopilación de datos
• Procesamiento y Limpieza de Datos
Pasos para el preprocesamiento de datos
Tratamiento de datos faltantes y valores atípicos
• Análisis Exploratorio de Datos (AED)
Técnicas para AED
Visualización de datos de moda
• Aprendizaje Automático para la Moda
Introducción a los conceptos de aprendizaje automático
Aprendizaje supervisado vs. no supervisado en contextos de moda
• Analítica Predictiva en la Moda
Técnicas de pronóstico de demanda
Modelos de predicción de tendencias
• Conocimientos del Cliente y Personalización
Segmentación y perfilamiento
Sistemas de recomendación en el comercio minorista de moda
• Aplicaciones de IA en la Moda
Aplicaciones de visión por computadora: reconocimiento de imágenes y asistencia de estilo
Procesamiento del lenguaje natural para el análisis de tendencias
• Análisis de Sentimientos y Redes Sociales
Técnicas para el análisis de sentimientos
Medición del compromiso de la marca y tendencias en redes sociales
• Gestión de Inventario y Analítica de la Cadena de Suministro
Optimización de niveles de inventario con análisis de datos
Optimización de la cadena de suministro impulsada por IA
• Consideraciones Éticas y Privacidad de Datos
Cuestiones de privacidad en el análisis de datos de moda
IA ética y sus implicaciones en la moda
• Estudios de Caso y Aplicaciones Reales
Historias de éxito de empresas líderes en moda
Proyectos prácticos y discusiones en grupo
• Tendencias Futuras en el Análisis de Datos de Moda
Tecnologías emergentes y su posible impacto
Preparación para el futuro del análisis de moda
• Revisión del Curso y Proyecto Final
Revisión de conceptos clave
Desarrollo y presentación de un proyecto final integral en análisis de datos de moda

---

Impartido por

365 Careers

---

Materias

Data Science