Introduction to AI for Cybersecurity
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Introduction to AI for Cybersecurity
This course is part of AI for Cybersecurity Specialization
Instructor: Lanier Watkins
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What you'll learn
Use AI techniques to detect and mitigate various cyber threats, protecting digital assets and data.
Develop and apply machine learning models to identify, classify, and filter spam and phishing emails.
Implement AI-driven biometric solutions like keystroke dynamics and facial recognition to enhance user authentication security.
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There are 4 modules in this course
In "Introduction to AI for Cybersecurity," you'll gain foundational knowledge of how artificial intelligence (AI) is transforming the field of cybersecurity. This course covers key AI techniques and how they can be applied to enhance security measures, detect threats, and secure digital systems. Learners will explore hands-on implementations of AI models using tools like Jupyter Notebooks, allowing them to detect spam, phishing emails, and secure user authentication using biometric solutions.
What makes this course unique is its focus on real-world applications, blending AI theory with practical skills relevant to today's cybersecurity challenges. By the end of the course, you'll have developed the ability to use AI to address cyber threats such as email fraud and fake logins, and will be equipped with practical skills to protect digital assets in a rapidly evolving technological landscape. Whether you're a cybersecurity professional or someone seeking to expand your skills in AI, this course provides a critical understanding of how AI can be leveraged to mitigate security risks and keep systems secure.
This course will guide you through the ML development process and its vital applications in combating cyber threats. We’ll explore the challenges posed by technological advancements, examine AI’s role in spam filtering and email threat detection, and implement key algorithms like decision trees and Naïve Bayes. Additionally, you’ll learn how biometric solutions, such as keystroke dynamics and facial recognition, can enhance user authentication security.
What's included
2 readings
2 readings•Total 12 minutes
- Course Overview•10 minutes
- Instructor Biography - Lanier Watkins•2 minutes
In this module, we will discuss the background of artificial intelligence (AI) and provide a brief overview. Also, in this module and every module, we will take a hands-on approach to learning how to use AI for cybersecurity.
What's included
2 videos3 readings3 assignments
2 videos•Total 17 minutes
- Artificial Intelligence Background and Overview•10 minutes
- A Hands-On Look at Several Machine Learning Algorithms•7 minutes
3 readings•Total 70 minutes
- Reading References•15 minutes
- Reading References•15 minutes
- Self-Reflective Reading: Hands-On ML Examples and Development Process•40 minutes
3 assignments•Total 90 minutes
- AI for Cybersecurity Professionals•60 minutes
- Introduction to Artificial Intelligence for Cybersecurity•15 minutes
- Practical Machine Learning Algorithms for Cybersecurity•15 minutes
In this module, we shall discuss the detection of email threats using AI. Also, we will implement hands-on examples of the use of various ML techniques to detect email threats such as perceptron for spam filtering, support vector machine for spam filtering, regression and decision tree algorithms for spam filtering, and the use of Naïve Bayes ML algorithm and natural language processing for spam filtering.
What's included
5 videos3 readings3 assignments
5 videos•Total 15 minutes
- Detecting Email Cyber Threats with AI•4 minutes
- Perceptron Spam Filter Example•2 minutes
- Support Vector Machine (SVM) Spam Filter Example•3 minutes
- Phishing Detection with Regression and Trees•4 minutes
- Naive Bayes Spam Filter Example•1 minute
3 readings•Total 70 minutes
- Reading References•15 minutes
- Reading References•15 minutes
- Self-Reflective Reading: Bridging Theory and Practice in Cybersecurity•40 minutes
3 assignments•Total 90 minutes
- Ham or Spam? Detecting Email Cybersecurity Threats with AI•60 minutes
- AI Techniques for Detecting Email Threats•15 minutes
- Advanced Spam Filtering Methods and Phishing Detection•15 minutes
In this module, we will discuss the background of threats against user authentication. Also, we will explore hands-on implementations of fake login detection analytics using biometrics.
What's included
2 videos3 readings3 assignments1 ungraded lab
2 videos•Total 12 minutes
- Securing User Authentication•5 minutes
- Keystroke and Facial Recognition Biometric Authentication•6 minutes
3 readings•Total 70 minutes
- Reading References•15 minutes
- Reading References•15 minutes
- Self-Reflective Reading: Authentication is Paramount•40 minutes
3 assignments•Total 90 minutes
- Securing User Authentication •60 minutes
- Understanding and Securing User Authentication Threats•15 minutes
- Implementing Biometric Solutions: Keystroke and Facial Recognition•15 minutes
1 ungraded lab•Total 60 minutes
- Practice Lab: Detecting IoT Malware Behavior in Network Traffic•60 minutes
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Reviewed on Feb 8, 2026
Very educative, informative and user friendly with tons of examples.
Reviewed on Mar 5, 2025
The necessary material, good questions. Thank you.
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