Developing Data and AI Applications for Retail
Transform retail with data analytics and AI. Build applications that enhance customer experiences, optimize inventory, and drive informed decisions.
AI Usage in Retail
Introduction
Overview
Examples of AI in Retail
Examples of AI in Retail Cont.
Introduction
Overview
ML Review
Identify a Regression Scenario
Microsoft Azure Designer Tool
Regression Steps
Regression Real World Examples
Demo Intro
Policies 1
Policies 2
ML Service Creation
Navigate to ML Studio
ML Studio Tour
Computing Instance
Designer Tool Tour
Pipeline Creation 1
Pipeline Creation 2
Submitting Pipeline
Evalution Metrics
Inference Pipeline
Inference Pipeline - Enter Manual Data
Inference Pipeline Submission
Setting Up Endpoint
Swagger UI
Prediction on New Unseen Data
Introduction to NLP in Retail
Overview
Language Service / Studio
Configure Settings for Language Studio
Examples of NLP in Retail
Retail Demonstration Intro
Language Service Creation
Language Studio Navigation
Azure's Pre-trained Sentiment Analysis Model
Types of Computer Vision
Microsoft Azure
Optical Character Recognition
OCR and Text Analysis
OCR and Translation
AI in Retail Scenario
Microsoft Azure Resource Creation
OCR in Retail
Introduction
Sephora Virtual Artist
IKEA
Rufus
Walmart
Nike
Congratulations on completing this course!
Build real-world AI applications to solve key challenges in the retail industry
Gain hands-on experience with Azure AI, NLP, and computer vision tools
Use data to enhance customer experience, personalize marketing, and optimize
Self-paced, online learning with weekly live support sessions
Work with real retail data to extract insights and drive strategic decisions
Understand the ethical use of customer data in AI applications