Cybersecurity with Artificial Intelligence
Intermediate
About the Course
AI in Cybersecurity Operations
Explore how AI and machine learning integrate into cybersecurity operations, covering AI-powered threat detection, log analysis, anomaly detection, incident response, and SOC automation. Gain theoretical grounding and hands-on practice with up-to-date AI security tools applied to real-world scenarios.
Learning Outcomes
- Master AI-powered threat detection and anomaly identification for stronger SOC operations
- Analyze large-scale logs with AI to detect suspicious activity faster
- Develop defenses against deepfakes and AI-driven phishing
- Build SOC automation workflows to boost efficiency and response speed
- Apply leading AI security tools directly to workplace scenarios
Who Should Attend?
- Network and Security Specialists
- Cybersecurity Professionals
- SOC Analysts
- IT Professionals
Prerequisites
- Basic interest in the field
- Computer and internet access
Hands-On AI for SOC
Use up-to-date AI security tools and practice on real-world scenarios to accelerate threat detection and incident response.
Course Content
AI in Cybersecurity: Operations, Analytics, and Incident Response
A practical program on applying AI and machine learning to cybersecurity, covering threat detection, log analytics, SOC automation, incident response, next‑generation attack defense, and governance—reinforced by hands-on labs with leading security tools.
- Microsoft Security Copilot
- ChatGPT
- Claude
- Splunk AI
- CrowdStrike
- Darktrace
- SentinelOne Purple AI
1 Module 1 Fundamentals of AI in Cybersecurity and Use Cases
- Position AI/ML within modern security operations
- Explain core AI and ML concepts for security
- Map key cybersecurity use cases powered by AI
- Identify benefits and limitations of AI approaches
Duration: 75 minutes
2 Module 2 AI-Powered Threat Detection and Anomaly Identification
- Apply anomaly detection and behavioral analytics
- Identify suspicious activities across network and endpoints
- Tune detection thresholds to reduce false positives
- Evaluate model performance for threat detection
Duration: 90 minutes
3 Module 3 Log Analysis and Data Correlation
- Process and normalize large-scale log data
- Use AI to correlate events and extract insights
- Integrate with SIEM for end-to-end workflows
- Prioritize signals for investigation
Duration: 75 minutes
4 Module 4 AI in SOC Operations and Automation
- Automate alert triage and enrichment
- Prioritize incidents with AI-driven scoring
- Design playbooks for repetitive SOC tasks
- Measure operational efficiency improvements
Duration: 90 minutes
5 Module 5 AI-Powered Incident Response and Threat Intelligence
- Accelerate response actions with AI assistance
- Generate and operationalize threat intelligence
- Leverage generative AI for investigation support
- Improve accuracy and speed in response workflows
Duration: 75 minutes
6 Module 6 Next-Generation Attacks: AI-Based Threats and Defense Strategies
- Assess deepfakes and content manipulation risks
- Detect AI-driven phishing and social engineering
- Understand automated attack techniques
- Apply layered defenses and detection strategies
Duration: 75 minutes
7 Module 7 AI Integration and Governance in Security Processes
- Integrate AI tools into existing security operations
- Address data security and privacy requirements
- Monitor model reliability and performance
- Implement governance and policy controls
Duration: 60 minutes
8 Module 8 Advanced Security Analytics and Continuous Improvement
- Define security analytics metrics and KPIs
- Detect and remediate model drift
- Tune and scale AI-powered detections
- Establish continuous improvement cycles
Duration: 60 minutes
