The AI and Machine Learning in Cyber Defense in Amman is a forward-focused training course designed to help professionals harness AI for advanced cybersecurity strategies.
From:
19-01-2026
From:
03-08-2026
Course Overview
Cybersecurity threats are growing faster than human analysts can manage. Artificial intelligence (AI) and machine learning (ML) have become critical in defending systems by automating detection, analyzing anomalies, and predicting future threats.
This AI and Machine Learning in Cyber Defense Training Course introduces participants to the practical applications of AI and ML in cybersecurity. It covers anomaly detection, predictive analytics, behavioral modeling, and AI-powered incident response.
Through labs, case studies, and simulations, participants will learn to design AI-driven defense strategies that improve security operations, reduce response time, and strengthen resilience against advanced cyberattacks.
Course Benefits
Understand AI and ML applications in cyber defense.
Enhance detection of anomalies and advanced threats.
Automate cybersecurity monitoring and response.
Apply predictive analytics for threat intelligence.
Improve SOC efficiency and cyber resilience.
Course Objectives
Explore fundamentals of AI and ML in cybersecurity.
Apply ML models for anomaly and intrusion detection.
Integrate AI into SOC operations.
Develop predictive models for cyber threat intelligence.
Understand ethical and governance challenges in AI defense.
Review case studies of AI-powered security tools.
Build strategies for AI-driven resilience.
Training Methodology
The course blends expert-led lectures, AI/ML labs, simulations, and interactive workshops. Participants will practice building and applying machine learning models in cybersecurity scenarios.
Target Audience
Cybersecurity analysts and SOC teams.
Data scientists working in security operations.
IT and network security professionals.
Executives seeking to leverage AI for security strategy.
Target Competencies
AI and ML in cyber defense.
Threat prediction and anomaly detection.
SOC automation with AI tools.
Cybersecurity resilience strategies.
Course Outline
Unit 1: Introduction to AI and ML in Cybersecurity
Role of AI and ML in cyber defense.
Benefits and limitations of AI applications.
Case studies of AI in security operations.
Ethical and governance considerations.
Unit 2: Machine Learning Models for Cyber Defense
Supervised vs. unsupervised learning in security.
Classification and clustering for intrusion detection.
Feature engineering in cybersecurity data.
Lab: building a simple ML intrusion detector.
Unit 3: Anomaly Detection and Behavioral Analytics
Detecting unusual activity in networks.
User and entity behavior analytics (UEBA).
ML models for insider threat detection.
Practical anomaly detection exercise.
Unit 4: AI-Powered SOC and Incident Response
Automation in SOC operations.
AI for log analysis and SIEM integration.
AI-driven incident response strategies.
Simulation: SOC automation with AI.
Unit 5: Future of AI in Cyber Defense
Predictive analytics for cyber threat intelligence.
Deep learning and advanced AI in cyber defense.
Post-quantum and AI challenges.
Future trends in AI-powered security.
Ready to harness AI for cyber defense?
Join the AI and Machine Learning in Cyber Defense Training Course with EuroQuest International Training and gain the expertise to build intelligent, resilient cybersecurity systems.
The AI and Machine Learning in Cyber Defense Training Courses in Amman provide professionals with advanced expertise in applying artificial intelligence and machine learning to detect, prevent, and respond to cyber threats. Designed for cybersecurity specialists, data scientists, IT managers, and network analysts, these programs equip participants with the technical and analytical skills required to build intelligent, adaptive, and proactive cyber defense systems.
Participants gain a deep understanding of how AI and machine learning (ML) enhance cybersecurity operations by automating threat detection, improving incident response, and predicting potential vulnerabilities. The courses cover key topics such as anomaly detection, behavioral analytics, neural networks, natural language processing, and automated malware classification. Through hands-on labs and real-world simulations, attendees learn to implement AI-driven security solutions that strengthen resilience against evolving cyberattacks.
These cyber defense and AI security training programs in Amman combine cutting-edge technology with strategic cyber risk management. Participants explore how to integrate AI and ML models into existing security infrastructures, utilize predictive analytics to forecast attacks, and optimize security operations centers (SOCs) through intelligent automation. The curriculum also addresses the ethical and regulatory considerations of AI in cybersecurity, including data privacy, algorithmic transparency, and compliance with international standards.
Attending these training courses in Amman provides professionals the opportunity to learn from global cybersecurity experts in a collaborative and innovation-driven environment. The city’s growing reputation as a regional technology hub offers an ideal backdrop for exploring the convergence of AI and digital security. By completing this specialization, participants will be equipped to leverage artificial intelligence and machine learning to revolutionize their organization’s cyber defense capabilities—ensuring smarter threat detection, faster response times, and stronger protection in the face of evolving digital threats.