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Starts 18 June 2025 08:23

Ends 18 June 2025

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AI and Machine Learning in Cybersecurity

Discover how to leverage AI and machine learning for cybersecurity challenges, from anomaly detection to combating ransomware, malware, and phishing, including using large language models.
via Pluralsight

659 Courses


1 hour 6 minutes

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Overview

Explore this fascinating field and develop the skills to leverage AI in your cybersecurity challenges. In this course, AI and Machine Learning in Cybersecurity, you’ll learn to use AI to leverage your cybersecurity skills.

First, you’ll explore machine learning and anomaly detection. Next, you’ll discover AI cybersecurity strengths like ransomware, malware, and phishing.

Finally, you’ll learn how to leverage large language models for enhancing cybersecurity. When you’re finished with this course, you’ll have the skills and knowledge of AI cybersecurity needed to enhance your skills and abilities in cybersecurity.

Syllabus

  • Introduction to AI in Cybersecurity
  • Overview of AI and machine learning concepts
    Importance of AI in the cybersecurity landscape
  • Machine Learning Techniques for Cybersecurity
  • Supervised and unsupervised learning methods
    Feature selection and data preprocessing
    Model evaluation and performance metrics
  • Anomaly Detection
  • Types of anomalies in cybersecurity
    Techniques for anomaly detection
    Implementing anomaly detection models
  • AI Applications in Ransomware Detection
  • Understanding ransomware behavior
    Machine learning models for ransomware detection
    Case studies and real-world applications
  • Malware Analysis with AI
  • Static and dynamic analysis of malware
    Machine learning techniques for malware classification
    Advanced threat detection using AI
  • AI Strategies for Phishing Detection
  • Identifying phishing attacks
    Leveraging AI to detect phishing attempts
    Implementations and practical tools
  • Leveraging Large Language Models for Cybersecurity
  • Introduction to large language models (LLMs)
    Using LLMs for threat intelligence and analysis
    Enhancing incident response with LLMs
  • Ethical Considerations and Challenges
  • Addressing biases in AI models
    Ethical use of AI in cybersecurity
    GDPR and data privacy concerns
  • Hands-on Labs and Projects
  • Practical exercises for anomaly detection
    Building models for ransomware and malware detection
    Phishing detection with natural language processing
  • Conclusion and Future Trends
  • Emerging AI technologies in cybersecurity
    Future of AI-driven cybersecurity solutions
    Continuous learning and upskilling resources
  • Assessment and Certification
  • Course project and practical assessment
    Final exam and course certification criteria

Taught by

Kevin Cardwell


Subjects

Information Security (InfoSec)