The Data Science of Marketing

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English
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2-3 hours worth of material
selfpaced

Overview

Discover how to leverage R, Python, and Tableau to gain robust insights from large data sets.
Introduction
  • Welcome
  • Data science for marketing
  • Obtain data
1. Software Installation
  • Install R
  • Install Python
  • Install Tableau
  • Orientation to UI for R, Python, and Tableau
  • Exercise files
2. Data, Exploratory Analysis, and Performance Analysis
  • Overview and case study
  • Exploratory analysis with R
  • Exploratory analysis with Python
  • Exploratory analysis with Tableau
  • Pros and cons
3. Inference and Regression Analysis
  • Overview and case study
  • Regression with R
  • Regression with Python
  • Regression with Tableau
4. Prediction
  • Overview and case study
  • Prediction with R
  • Prediction with Python
  • Prediction with Tableau
5. Cluster Analysis
  • Overview and case study
  • Cluster Analysis with R
  • Cluster Analysis with Python
  • Cluster Analysis with Tableau
6. Conjoint Analysis
  • Overview and case study
  • Conjoint analysis with R
  • Conjoint analysis with Python
  • Conjoint analysis with Tableau
7. Best Practices
  • Agile marketing
  • Design and conduct market experiments
  • Stakeholder alignment
Conclusion
  • Next steps

Syllabus

Introduction
  • Welcome
  • Data science for marketing
  • Obtain data
1. Software Installation
  • Install R
  • Install Python
  • Install Tableau
  • Orientation to UI for R, Python, and Tableau
  • Exercise files
2. Data, Exploratory Analysis, and Performance Analysis
  • Overview and case study
  • Exploratory analysis with R
  • Exploratory analysis with Python
  • Exploratory analysis with Tableau
  • Pros and cons
3. Inference and Regression Analysis
  • Overview and case study
  • Regression with R
  • Regression with Python
  • Regression with Tableau
4. Prediction
  • Overview and case study
  • Prediction with R
  • Prediction with Python
  • Prediction with Tableau
5. Cluster Analysis
  • Overview and case study
  • Cluster Analysis with R
  • Cluster Analysis with Python
  • Cluster Analysis with Tableau
6. Conjoint Analysis
  • Overview and case study
  • Conjoint analysis with R
  • Conjoint analysis with Python
  • Conjoint analysis with Tableau
7. Best Practices
  • Agile marketing
  • Design and conduct market experiments
  • Stakeholder alignment
Conclusion
  • Next steps

Taught by

Chris DallaVilla

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