Descriptions
AI for Cyber Security : Threat Detection, SOC Automation, 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. Modules cover foundations of AI in security, ML for anomaly and IDS enhancement, NLP for threat intelligence enrichment, AI‑powered SOAR and playbook automation, incident response optimisation, user behaviour analytics and graph‑based risk scoring, AI‑driven malware classification using sandboxing and EMBER, cloud and network security use cases, endpoint detection automation and federated learning, ethical limitations such as bias and false positives, and a capstone project to design an AI‑augmented SOC workflow. By the end of this course you’ll be able to build, automate, and manage AI‑powered defence systems and apply them in cutting‑edge cybersecurity and AI operations roles.
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.
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.
Specificatoin of AI for Cyber Security : Threat Detection, SOC Automation
- Publisher : Udemy
- Teacher : Selfcode Academy
- Language : English
- Level : All Levels
- Number of Course : 76
- Duration : 23 hours and 34 minutes
Content of AI for Cyber Security : Threat Detection, SOC Automation
Requirements
- A basic understanding of cybersecurity or general IT concepts will be helpful but is not mandatory to start this course.
- No prior experience with AI, machine learning, or programming is required � all essential concepts are explained from scratch.
- Students will need access to a computer with an internet connection to explore hands-on labs, simulations, and AI-powered security tools.
- An eagerness to explore how Artificial Intelligence is revolutionizing cybersecurity and automation will help maximize learning outcomes.
Pictures
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File size
26.44 GB
