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In this course, you will :
- Understand data and analysis like you've never seen before, and be able to collaborate with data scientists in multidisciplinary settings.
- learn how to make the most of their contributions when collaborating with marketing and sales specialists
- Learn how to extract valuable insights from large data sets by utilising specific languages and tools.
- how to use R, Python, and Tableau to perform data modelling and performance evaluation
- When he delves into these concepts, he shares specific case studies from his own work with clients.
- shares three essential—and practical—best practises for data-driven marketing that you can use to improve your company's marketing performance.
Syllabus :
1. Software Installation
- Install R
- Install Python
- Install Tableau
- Orientation to UI for R, Python, and Tableau
2. Data, Exploratory Analysis, and Performance Analysis
- Exploratory analysis with R
- Exploratory analysis with Python
- Exploratory analysis with Tableau
- Pros and cons
3. Inference and Regression Analysis
- Regression with R
- Regression with Python
- Regression with Tableau
4. Prediction
- Prediction with R
- Prediction with Python
- Prediction with Tableau
5. Cluster Analysis
- Cluster Analysis with R
- Cluster Analysis with Python
- Cluster Analysis with Tableau
6. Conjoint Analysis
- Conjoint analysis with R
- Conjoint analysis with Python
- Conjoint analysis with Tableau
7. Best Practices
- Agile marketing
- Design and conduct market experiments
- Stakeholder alignment
