Advanced Malware and Network Anomaly Detection

This course is part of AI for Cybersecurity Specialization

Instructor: Lanier Watkins

What you'll learn

  •   Understand various types of malware and apply foundational analysis techniques to effectively detect and classify them.
  •   Implement advanced machine learning algorithms, including clustering and decision trees, for efficient malware detection.
  •   Explore anomaly detection techniques using botnet data and learn how to analyze network traffic for unusual patterns.
  •   Collaborate and present research findings on current trends in network anomaly detection, enhancing communication and analytical skills.
  • Skills you'll gain

  •   Supervised Learning
  •   Threat Detection
  •   Machine Learning Methods
  •   Network Analysis
  •   System Design and Implementation
  •   Network Security
  •   Malware Protection
  •   Cybersecurity
  •   Machine Learning Algorithms
  •   Intrusion Detection and Prevention
  •   Machine Learning
  •   Continuous Monitoring
  •   Machine Learning Software
  •   Anomaly Detection
  •   Microsoft Windows
  •   Performance Testing
  • There are 4 modules in this course

    What sets this course apart is its emphasis on practical, project-based learning. By applying your knowledge through hands-on implementations and collaborative presentations, you will develop a robust skill set that is highly relevant in today’s cybersecurity landscape. Completing this course will prepare you to effectively identify and mitigate threats, making you a valuable asset in any cybersecurity role. With the rapid evolution of cyber threats, this course ensures you stay ahead by leveraging the power of AI for robust cybersecurity measures.

    Malware Threats Detection Part 1

    Malware Threats Detection Part 2

    Network Anomaly Detection with AI

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