What you'll learn

Skills you'll gain

There are 12 modules in this course

With the growing amount of data and applications of machine learning in marketing, we can easily find examples of the usage of machine learning in marketing efforts. Companies are starting to use machine learning to better understand customer behaviors and identify different customer segments based on their activity patterns. Many organizations also use machine learning to predict future customer behaviors, such as what items they are likely to purchase, which websites they are likely to visit, and who are likely to churn. With endless use cases of machine learning for marketing, companies of all sizes can benefit from using machine learning for their marketing efforts. To succeed in this course, you should have a basic understanding of Python. You will also need certain software requirements, including an Anaconda navigator.

Getting Started With Supervised Learning in Marketing 

Weekly Summative Assessment: Supervised Learning in Marketing 

Deriving Insights from Data 

Product Recommender System 

Weekly Summative Assessment: Deriving Insights from Data and Product Recommender System 

Personalized Marketing 

Customer Lifetime Value  

Weekly Summative Assessment: Personalized Marketing and Customer Lifetime Value

Retaining Customers 

Deployment of Supervised Learning Models 

Weekly Summative Assessment: Retaining customers and Deployment of Supervised Learning Models 

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