Overview
Discover how to leverage R, Python, and Tableau to gain robust insights from large data sets.
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
- Next steps
Conclusion