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AI with Cyber Security
AI-powered security systems for threat detection, anomaly analysis, and zero-trust protection.
QuantQ Vision// ai-with-cyber-security
Full course details & curriculum
AI-powered security systems for threat detection, anomaly analysis, and zero-trust protection.
Learning outcomes
- Build anomaly detection systems
- Design zero-trust reference architectures
- Run AI-assisted red/blue team drills
Curriculum — module by module
Threat Detection
Detect attacks in logs, network, and endpoint telemetry.
Lessons
- Telemetry pipelines & data modeling
- Supervised detection with labeled attacks
- SIEM/SOAR integration patterns
- Reducing false positives
You will be able to
- Deploy a detection model into a SOC pipeline
- Measure precision, recall, and MTTR impact
Anomaly Analysis
Find the unknown-unknowns with unsupervised learning.
Lessons
- Statistical vs. deep anomaly methods
- User & entity behavior analytics (UEBA)
- Explainability for alerts
- Feedback loops with analysts
You will be able to
- Ship a UEBA baseline for a real dataset
- Deliver analyst-ready explainable alerts
Zero-Trust Architecture
Design AI-assisted zero-trust reference architectures.
Lessons
- Identity, device, and workload trust
- Policy-as-code with AI risk scoring
- Micro-segmentation strategies
- Continuous verification patterns
You will be able to
- Produce a zero-trust reference architecture
- Integrate AI risk scoring into access policy