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Digital Advertising & Marketing 101: Take The Complete Guide

18.8 hours
All Levels

How do consumers see your brand relative to your competitors? …

What you'll learn
From one-off customer satisfaction surveys to brand tracking surveys that are administering on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers.
In Analytic Methods for Survey Data, statistical learners will become familiar with established methods for converting survey responses to insights that can support marketing decisions.
Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling.

Mastering Makeup Application Techniques at Home

2 hours
All Levels

Are you interested in improving your makeup application skills, or …

What you'll learn
Improving your makeup application skills
Pursuing a career as a professional Makeup Artist

Natural Skincare: Easy Herbs and Recipes for Younger Skin

2 hours
All Levels

Are you interested in improving your makeup application skills, or …

What you'll learn
Improving your makeup application skills
Pursuing a career as a professional Makeup Artist

Professional Everyday & Bridal Makeup

2 hours
All Levels

Are you interested in improving your makeup application skills, or …

What you'll learn
Improving your makeup application skills
Pursuing a career as a professional Makeup Artist

Survey analysis to Gain Marketing Insights

18.8 hours
All Levels

How do consumers see your brand relative to your competitors? …

What you'll learn
From one-off customer satisfaction surveys to brand tracking surveys that are administering on a continuous basis, they provide the information that marketers need to understand how their products, services and brands are seen by consumers.
In Analytic Methods for Survey Data, statistical learners will become familiar with established methods for converting survey responses to insights that can support marketing decisions.
Techniques discussed include factor analytics, cluster analysis, discriminant analysis and multi-dimensional scaling.
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