Detecting Email threats using AI (Lecturer Notes)

This session explains how to use machine-learning algorithms to detect spam and phishing emails. Students will learn how email security solutions can benefit from using ML and how to design such a solution.

In-class practices:

A. Students follow the steps of the machine learning code for email threat detection. Read the descriptions and instructions. Python code for email threats.
The lecturer shows the expected results for each section; students write the code, and they learn why and how they should do that. Finally, the lecturer makes sure that all the students get the same result and understand that part. The aim of this practice is how to develop a simple machine-learning code to detect phishing/spam emails. In the previous session, students learned how they (as users) could detect phishing by spotting phishing signs (e.g., fake sender email’s domain name), and now they must learn how AI can do that for us. The same signs can be used as the machine learning model’s features.

Lecturer Notes:

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Dataset:

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Code Explanation video