Overview What You Will Learn Curriculum Instructor

Course Overview

In today’s digital threat landscape, phishing remains one of the most persistent and dangerous forms of cyberattacks. This course is designed to equip you with a deep understanding of how phishing tactics have evolved and how emerging technologies like Machine Learning (ML) and Generative AI (Gen AI) are reshaping the way these threats are identified and mitigated. Whether you're a cybersecurity professional, a data enthusiast, or someone keen on leveraging AI for defense, this course will guide you step-by-step in using AI to tackle phishing head-on. 

This course begins with a foundational look at phishing attacks and their evolution, helping you recognize how these threats have become more deceptive over time. You’ll then dive into the applications of ML and Gen AI in phishing detection, learning how to build and train ML models tailored for this purpose. You’ll explore how to simulate phishing emails and detect them using large language models (LLMs), build a GPT-powered phishing detection app, and identify phishing content with custom models. The course also covers AI-based URL and fake website detection, showcases a chatbot-driven phishing detection case study, and wraps up with real-world examples, best practices, and insights into future trends in AI-powered phishing threats. 

By the end of this course, you’ll be able to build and apply AI-driven tools to detect, simulate, and defend against phishing attacks effectively. 

What You Will Learn

  • Understand the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML) in phishing defense.
  • Explore various types of phishing attacks , including spear-phishing , vishing and business email compromise with real-world case studies.
  • Learn how AI and NLP techniques classify and detect phishing emails using machine learning models.
  • Train and evaluate ML models for phishing email classification, including feature engineering and performance analysis.
  • Use Large Language Models (LLMs) to simulate phishing attacks and develop AI-driven phishing detection systems.

Program Curriculum

  • Introduction to Phishing Attacks
  • Chapter 1 Quiz

  • Introduction to ML and Application of ML in Phishing Detection
  • Introduction to Generative AI and Its Application in Phishing Detection
  • Applying AI and Machine Learning in Cybersecurity - Lab
  • Chapter 2 Quiz

  • Develop and Train ML Models for Phishing Detection
  • Machine Learning for Cybersecurity - Lab
  • Chapter 3 Quiz

  • Simulating Phishing Emails Using LLMs
  • Detecting Phishing Emails Using LLMs
  • Building an LLM-Powered Phishing Detection App
  • Identify Phishing Content Using Custom GPT
  • Applied AI in Cybersecurity: Phishing Detection and Analysis - Lab
  • Chapter 4 Quiz

  • Detect Phishing Websites Using URL Classification Models
  • Applying Machine Learning for Cybersecurity
  • Chapter 5 Quiz

  • Phishing Detection with LLM Chatbot - Case Study
  • AI-Powered Cybersecurity Training - Lab
  • Chapter 6 Quiz

  • AI on the Frontlines: Real-world Case Studies
  • Best Practices for AI-based Phishing Defense
  • Future Trends: AI-powered Phishing Threats
  • Chapter 7 Quiz
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Instructor

Manas Dasgupta

Manas holds an MSc in AI-ML from Liverpool John Moores University (LJMU), UK. His expertise includes Generative AI (RAG application development using frameworks like LangChain and LlamaIndex), Machine Learning, Data Science, and Predictive Analytics, with a focus on techniques such as Supervised and Unsupervised Learning, Deep Neural Networks, and Clustering.

His research focuses on Natural Language Processing (NLP) using Deep Learning methods like Siamese Networks, Encoder-Decoder techniques, and Language Embeddings (e.g., BERT).

With over 20 years of experience in IT, primarily in Financial Services, Manas has developed solutions for top banks and institutions, including Natwest, ANZ, KBC, Visa, and Experian.

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