Free Download AI-Driven Cybersecurity AutomationPublished 2/2026
Created by Data Science Academy, School of AI
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels |
Genre: eLearning |
Language: English |
Duration: 75 Lectures ( 8h 31m ) |
Size: 5 GB
✓ Design and implement AI-driven cybersecurity automation for cloud, network, endpoint, and identity environments using modern enterprise security principles.
✓ Build autonomous threat detection and response workflows while understanding how and why automation fails - including feedback loops, cascade failures.
✓ Defend AI security systems themselves by identifying and mitigating data poisoning, model evasion, automation abuse, and adversarial attacks
✓ Apply human-in-the-loop design, kill switches, and rollback systems to ensure safe, controlled, and accountable security automation.
✓ Monitor, audit, and explain AI security decisions to maintain trust, transparency, and governance in automated defense systems.
✓ Evaluate and secure training data and AI pipelines to prevent long-term degradation of detection accuracy and system reliability.
✓ Design resilient, enterprise-grade AI security architectures that balance speed, scale, safety, and explainability.
Requirements● Basic understanding of cybersecurity concepts such as networks, endpoints, cloud services, or identity systems
● Familiarity with general IT or cloud environments (AWS, Azure, GCP, or on-prem concepts)
● Interest in AI, automation, or security engineering
● Willingness to think architecturally about systems and risk
Description"This course contains the use of artificial intelligence"
Cybersecurity has entered a new era. Static rules, manual triage, and reactive defenses are no longer enough to protect modern cloud-native, distributed, and AI-powered systems. Attackers now operate at machine speed - and defenders must do the same, without sacrificing safety, trust, or control.
AI-Driven Cybersecurity Automation is a comprehensive, enterprise-grade course designed to teach you how to design, deploy, secure, and govern autonomous cyber defense systems. This course goes far beyond basic AI or security concepts. It shows you how real organizations automate detection and response, how those systems fail in practice, and how to build resilient, explainable, and trustworthy AI defenses.
You will learn how AI models detect threats, how automated containment and response systems operate, and how cloud, network, endpoint, and identity automation work together in modern security architectures. Just as importantly, you'll explore the hidden risks of automation - including feedback loops, cascade failures, over-automation outages, and adversarial abuse of AI systems.
Unlike surface-level courses, this program treats AI as a first-class security asset that must itself be defended. You'll dive deep into attacks against AI security systems, including data poisoning, model evasion, training data compromise, and automation manipulation. You'll then learn how to counter these threats using human-in-the-loop design, kill switches, rollback systems, decision monitoring, and explainability frameworks.
This course is structured like a real enterprise security program, not a theoretical lecture series. Every section builds toward one critical goal
Automate cyber defense safely, at scale, and with accountability.
Who this course is for■ Cybersecurity engineers, analysts, and SOC professionals who want to move beyond manual detection and learn how AI-powered automation is actually designed, deployed, and governed.
■ Cloud engineers, platform engineers, and DevOps professionals who are responsible for securing dynamic cloud and hybrid environments and want to understand autonomous security controls.
■ Security architects and technical leaders who need to design safe, scalable, and explainable AI-driven defense systems.
■ AI / ML engineers and data professionals who are building or supporting security-related AI systems and want to understand real security threats against AI models, pipelines, and data.
■ Product managers and technical decision-makers working on security, AI, or automation products who need a deep understanding of risk, trust, and governance in AI-driven defenses.
■ Students and career switchers with a foundational understanding of IT, cloud, or security who want to future-proof their skills and enter AI-powered cybersecurity roles.
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