Become a Citizen Data Scientist
Marketing Perspective
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Over 1,500 students from 100 countries

Understand your customer : Profiling, Segmentation, Targeting and Recommendation using Microsoft Azure ML, SQL, Power BI

Section 1

Introduction

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1. Welcome to the course
2. Set the expectations
3. Citizen Data Scientist

Section 2

Lay the foundation

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4. Introduction
5. Definitions
6. Data Science Process
7. Data Science Toolbox
8. Setup the Lab Environment : Tools & Data
9. Microsoft Azure Machine Learning
10. Marketing Framework Analysis

Section 3

Explore

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11. Introduction
12. Case study : Adventure Works
13. SQL Basics
14. Install Adventure Works Database
15. Lab 1: Data preparation using SQL
16. Lab 2: Customer Dashboard using Power BI

Section 4

Segment

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17. Introduction
18. Types of segmentation
19. Managerial Segmentation
20. Lab 3: Managerial segmentation using SQL

Section 5

Target

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21. Introduction
22. Classification Model : the Basics
23. Classification fundamental concept : Bias-Variance Tradeoff
24. Overview Diagram of Azure Machine Learning Studio
25. Lab 4: Bike Buyers targeting using Azure ML - Part 1
26. Lab 4: Bike Buyers targeting using Azure ML - Part 2

Section 6

Recommend

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27. Introduction
28. Recommendation System: Definition and types
29. Recommendation System: How it works
30. Lab 5: Next Best Offer using Azure ML - Part 1
31. Lab 5: Next Best Offer using Azure ML - Part 2

Section 7

Conclusion

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32. Wrap up
33. Resources

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