LSET’s AI-Powered Threat Detection & Incident Response Course provides a deep dive into the future of cybersecurity operations. This specialised programme blends artificial intelligence with practical threat detection and response strategies, preparing you to safeguard digital infrastructures in real time. You’ll explore AI and ML techniques for detecting anomalies, analysing logs, automating triage, and integrating intelligent response systems into modern SOC environments.
Technologies and Tools Covered in This Course
Splunk – A powerful platform for searching, monitoring, and analysing machine-generated data. Learn how to use Splunk with AI models to detect and classify threats automatically.
Elastic Stack (ELK) – Gain hands-on experience with Elasticsearch, Logstash, and Kibana to build real-time analytics dashboards and enable AI-powered event correlation.
Scikit-learn & TensorFlow – Implement machine learning models for behavioural analysis, anomaly detection, and pattern recognition in network traffic and system logs.
Zeek (formerly Bro) – A network analysis framework that supports advanced traffic inspection. Integrate Zeek logs with AI tools to build adaptive intrusion detection workflows.
TheHive & Cortex – Open-source incident response platforms for case management and automated analysis. Learn how to streamline SOC operations using AI-driven enrichment and correlation.
Jupyter Notebooks – Use notebooks to prototype, test, and explain ML-based security workflows, enabling full transparency and reproducibility.
MITRE ATT&CK Framework – Learn to map AI-detected events to known adversarial tactics and techniques for smarter response strategies.
Python for Security Automation – Develop scripts for automating detection rules, response playbooks, and log analysis tasks.
Career Accelerator Program
Premium Career-Ready Track
Note: Please note that all prices listed are exclusive of VAT. VAT will be charged separately and added to the total amount payable.
