Description
AI for Cyber Security: Threat Detection, SOC Automation provides a practical roadmap for applying artificial intelligence in modern cybersecurity operations. This training focuses on how AI, machine learning, and deep learning are transforming threat detection, security operations centers, and automated incident response.
You will explore real-world security use cases such as anomaly detection, intrusion detection enhancement, threat intelligence enrichment with NLP, SOAR automation, malware classification, user behavior analytics, and AI-driven incident response. Through hands-on labs and simulations, learners gain practical experience designing AI-augmented SOC workflows that reflect real industry environments. By the end, you will be equipped to build, automate, and manage intelligent defense systems for next-generation cybersecurity roles.
What You’ll Learn
- How AI, ML, and DL enhance modern cybersecurity operations
- Build AI-driven systems for threat detection and SOC automation
- Apply AI to malware analysis, incident response, and threat intelligence
- Design and simulate AI-augmented SOC workflows using real datasets
- Understand risks, limitations, bias, and false positives in AI security systems
Who This Is For
- SOC analysts and blue team professionals
- Incident responders and security engineers
- Cybersecurity professionals upskilling in AI automation
- AI and ML enthusiasts exploring cybersecurity applications
- Students and IT professionals transitioning into AI-driven security roles
Specifications
Publisher: Udemy
Instructor: Selfcode Academy
Language: English
Level: All Levels
Lectures: 76
Duration: 23 hours and 34 minutes
Requirements
- Basic IT or cybersecurity knowledge is helpful but not required
- No prior AI, machine learning, or programming experience needed
- Computer with internet access for labs and simulations
- Curiosity about AI-driven cybersecurity and automation
Rapidgator
File Size: 26.44 GB