[Update Course] AI for Cyber Security : Threat Detection, SOC Automation

AI for Cyber Security : Threat Detection, SOC Automation | Udemy [Update 12/2025]
English | Size:
Genre: eLearning

Created bySelfcode Academy

What you’ll learn:
Students will learn how Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming modern cybersecurity operations.
Students will gain practical skills to build and apply AI-driven systems for threat detection, SOC automation, and incident response.
Students will learn how to use popular AI-based cybersecurity tools such as Darktrace, CrowdStrike, and SOAR platforms for automated defense workflows.
Students will be able to design, simulate, and implement AI-augmented SOC workflows using real-world datasets and automation tools.
Understand the core principles of Artificial Intelligence and how they apply to cybersecurity.
Explore real-world use cases of AI in threat detection, malware analysis, and incident response.
Learn how AI enhances SOC operations, automates tasks, and supports decision-making.
Identify key risks, challenges, and limitations of using AI in cybersecurity environments.

Artificial Intelligence is redefining the future of cybersecurity — and this course is your complete roadmap to mastering it.

In AI for Cybersecurity: Threat Detection & SOC Automation, you’ll learn how AI, Machine Learning (ML), and Deep Learning (DL) are transforming how organisations detect, prevent, and respond to cyber threats.

This program blends real-world labs, tools, and automation workflows to prepare you for the next generation of AI-driven cybersecurity roles — from SOC analyst to security automation engineer.

What You’ll Learn Across Modules:

Module 1: Introduction to AI in Cybersecurity

Learn the foundations of AI, ML, and DL, explore their evolution, benefits, and challenges, and see how AI integrates into real-world SOC environments with tools like Darktrace and CrowdStrike.

Module 2: AI for Threat Detection

Understand machine learning for anomaly detection, supervised vs unsupervised learning, and how AI enhances IDS systems like Suricata for faster and smarter threat identification.

Module 3: AI for Threat Intelligence

Discover how Natural Language Processing (NLP) is used to analyse phishing data, automate enrichment with APIs such as VirusTotal and AbuseIPDB, and strengthen threat intel pipelines.

Module 4: AI for SOC Automation

Explore AI-powered SOAR platforms, playbook automation, and the balance between human and AI decision-making in modern security operations.

Module 5: AI for Incident Response

Learn how AI assists in decision-making, predicts breach impact, and optimises real-time alert management and forensic reconstruction.

Module 6: AI for User Behaviour Analytics (UBA)

Apply ML models to baseline user activity, detect insider threats, and use graph-based analytics for behavioural risk scoring.

Module 7: AI for Malware Analysis

Perform AI-driven malware classification using sandbox analysis, embeddings, and the EMBER dataset to detect and forecast malicious behaviour.

Module 8: AI in Cloud Security

Secure cloud environments using AI for misconfiguration detection, anomaly analysis, and posture management with AWS GuardDuty or Azure Defender.

Module 9: AI in Network Security

Analyse network traffic, identify DDoS patterns, and apply ML models for encrypted traffic analysis and zero-trust segmentation.

Module 10: AI in Endpoint Security

Automate EDR workflows, apply federated learning, and detect ransomware with behaviour-based AI models.

Module 11: Limitations & Ethical Considerations

Study bias, false positives, and privacy issues in AI systems to ensure ethical cybersecurity practices.

Module 12: Future of AI in Cybersecurity + Capstone Project

Design an AI-augmented SOC workflow, integrating tools, automation, and analytics for intelligent cyber defence.

By the end of this course, you’ll be able to build, automate, and manage AI-powered defence systems, preparing you for cutting-edge roles in cybersecurity and AI operations.

Who this course is for:
This course is designed for cybersecurity professionals who want to integrate AI into real-world defense, threat detection, and incident response workflows.
It is ideal for SOC analysts, blue teamers, and incident responders looking to upskill in AI-based security automation and intelligent threat detection.
t is also perfect for AI and machine learning enthusiasts who wish to understand their application in cybersecurity through hands-on labs and projects.
Students, IT professionals, and security engineers who aspire to transition into next-generation AI-driven SOC or automated defense roles will greatly benefit from this course.

DOWNLOAD FROM RAPIDGATOR

DOWNLOAD FROM TURBOBIT

If any links die or problem unrar, send request to
forms.gle/e557HbjJ5vatekDV9

[Update Course] AI for Cyber Security : Threat Detection, SOC Automation | Udemy

Leave a Comment Cancel reply