Supervised Learning and Its Applications in Marketing

Welcome to the Supervised Learning and Its Applications in Marketing course! Supervised learning is the process of making an algorithm to learn to map an input to a particular output. Supervised learning algorithms can help make predictions for new unseen data. In this course, you will use the Python programming language, which is an effective tool for machine learning applications. You will be introduced to the supervised learning techniques: regression and classification. The course will focus on the applications of these techniques in the domain of marketing. 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

• Apply Python as an effective tool for supervised learning techniques
• Develop and train supervised machine learning models for classification and regression tasks
• Interpret and analyze various applications of supervised learning in marketing
• Describe the deployment of machine learning models and the challenges encountered in the deployment

• No deep prior experience is required, but basic computer and internet skills are helpful
• Ability to read course instructions in English and complete short practice activities