LEARNING TRACKS

Educational Programs

Data Analytics Track

Master data collection, analysis, and visualization techniques specifically designed for fashion industry applications.

AI & Machine Learning

Learn to implement AI solutions, chatbots, and predictive models for fashion marketing and consumer insights.

Fashion Marketing

Combine traditional marketing principles with modern digital strategies and consumer behavior analysis.

Course Links & Resources

UPDATED

Access course materials, lecture recordings, and additional resources here.

COURSE CATALOG

Available Courses

Fashion Data Analytics Fundamentals

FML 301

3 CREDITS FALL BEGINNER

Introduction to data analytics in the fashion industry. Students learn Python programming, data manipulation with Pandas, and basic statistical analysis. Covers web scraping techniques for fashion e-commerce platforms and social media data collection.

Key Topics

Python Basics
Data Cleaning
Web Scraping
Statistical Analysis
Visualization
Project Work

AI Chatbots for Fashion Retail

FML 401

3 CREDITS SPRING ADVANCED

Advanced course on designing and implementing AI-powered chatbots for fashion retail. Students work with LLM APIs, learn prompt engineering, and develop conversational AI systems that enhance customer experience and drive sales.

Key Topics

LLM Integration
Prompt Engineering
Chatbot Design
User Experience
A/B Testing
Performance Metrics

Social Media Analytics for Fashion

FML 302

3 CREDITS FALL INTERMEDIATE

Comprehensive study of social media analytics in fashion marketing. Students analyze Instagram, TikTok, and other platforms to understand engagement patterns, influencer impact, and content strategy effectiveness using advanced statistical methods.

Key Topics

API Integration
Sentiment Analysis
Network Analysis
Trend Prediction
Influencer Analytics
Campaign ROI

Machine Learning for Fashion Marketing

FML 402

3 CREDITS SPRING ADVANCED

Apply machine learning algorithms to fashion marketing challenges. Topics include customer segmentation, recommendation systems, demand forecasting, and price optimization. Hands-on experience with scikit-learn, XGBoost, and deep learning frameworks.

Key Topics

Supervised Learning
Unsupervised Learning
Recommendation Systems
Neural Networks
Model Deployment
Ethics in AI

Consumer Behavior in Digital Fashion

FML 303

3 CREDITS BOTH INTERMEDIATE

Explore psychological and behavioral aspects of fashion consumption in digital environments. Combines theoretical frameworks with empirical research methods including surveys, experiments, and structural equation modeling (SEM).

Key Topics

Consumer Psychology
Research Design
SEM Analysis
Survey Methods
User Experience
Behavioral Economics

Fashion Industry Capstone Project

FML 499

6 CREDITS SPRING ADVANCED

Final integrative project where students work with real fashion companies to solve actual business challenges. Projects combine research, data analysis, and strategic recommendations. Culminates in presentation to industry partners.

Key Topics

Industry Partnership
Problem Definition
Research Execution
Data Analysis
Strategic Planning
Final Presentation
LEARNING PATH

Your Journey

1
Foundation
Learn programming and data basics
2
Application
Apply skills to fashion contexts
3
Specialization
Choose AI, analytics, or marketing track
4
Integration
Complete capstone project
SKILLS YOU'LL GAIN

Technical & Professional Skills

Python
R
Machine Learning
SQL
Web Scraping
Data Visualization
NLP
SEM
A/B Testing
API Integration
LLM Development
Research Design