Overview
Learn Data Analytics and Business Analysis for the Fashion Industry. Build a Smart and Data-driven Fashion Company!
Syllabus
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- Introduction to Data Analytics in Fashion
-- Overview of data analytics and its importance in fashion
-- Key data types and sources in the fashion industry
- Data Collection Methods
-- Understanding fashion data: sales, trend analysis, social media
-- Tools and techniques for data collection
- Data Processing and Cleaning
-- Data preprocessing steps
-- Dealing with missing data and outliers
- Exploratory Data Analysis (EDA)
-- Techniques for EDA
-- Visualizing fashion data
- Machine Learning for Fashion
-- Introduction to machine learning concepts
-- Supervised vs. unsupervised learning in fashion contexts
- Predictive Analytics in Fashion
-- Demand forecasting techniques
-- Trend prediction models
- Customer Insights and Personalization
-- Segmentation and profiling
-- Recommender systems in fashion retail
- AI Applications in Fashion
-- Computer vision applications: image recognition and styling assistance
-- Natural language processing for trend analysis
- Sentiment Analysis and Social Media
-- Techniques for sentiment analysis
-- Measuring brand engagement and trends from social media
- Inventory Management and Supply Chain Analytics
-- Optimizing inventory levels with data analytics
-- AI-driven supply chain optimization
- Ethical Considerations and Data Privacy
-- Privacy issues in fashion data analytics
-- Ethical AI and its implications in fashion
- Case Studies and Real-World Applications
-- Success stories from leading fashion companies
-- Hands-on projects and group discussions
- Future Trends in Fashion Data Analytics
-- Emerging technologies and their potential impact
-- Preparing for the future of fashion analytics
- Course Review and Final Project
-- Review of key concepts
-- Development and presentation of a comprehensive final project in fashion data analytics
Taught by
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On-Demand
