Course curriculum

    1. AI Usage in Retail

    2. Introduction

    3. Overview

    4. Examples of AI in Retail

    5. Examples of AI in Retail Cont.

    1. Introduction

    2. Overview

    3. ML Review

    4. Identify a Regression Scenario

    5. Microsoft Azure Designer Tool

    6. Regression Steps

    7. Regression Real World Examples

    8. Demo Intro

    9. Policies 1

    10. Policies 2

    11. ML Service Creation

    12. Navigate to ML Studio

    13. ML Studio Tour

    14. Computing Instance

    15. Designer Tool Tour

    16. Pipeline Creation 1

    17. Pipeline Creation 2

    18. Submitting Pipeline

    19. Evalution Metrics

    20. Inference Pipeline

    21. Inference Pipeline - Enter Manual Data

    22. Inference Pipeline Submission

    23. Setting Up Endpoint

    24. Swagger UI

    25. Prediction on New Unseen Data

    1. Introduction to NLP in Retail

    2. Overview

    3. Language Service / Studio

    4. Configure Settings for Language Studio

    5. Examples of NLP in Retail

    6. Retail Demonstration Intro

    7. Language Service Creation

    8. Language Studio Navigation

    9. Azure's Pre-trained Sentiment Analysis Model

    1. Types of Computer Vision

    2. Microsoft Azure

    3. Optical Character Recognition

    4. OCR and Text Analysis

    5. OCR and Translation

    6. AI in Retail Scenario

    7. Microsoft Azure Resource Creation

    8. OCR in Retail

    1. Introduction

    2. Sephora Virtual Artist

    3. IKEA

    4. Rufus

    5. Walmart

    6. Nike

    7. Congratulations on completing this course!

About this course

  • $850.00
  • 5 Modules
  • 15 hours of learning content

Course Highlights

  • 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