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Keep shoppingAI Security Engineer Bootcamp
Role Play
380 students
AI Security Engineer Bootcamp
Master AI Security: Model Threats, Data Protection, Supply Chain, Governance & Agentic AI Threat Modeling with MAESTRO
Created byRaghu The Security Expert
Last updated 6/2026
English
What you'll learn
- Identify and defend against AI model threats like prompt injection, poisoning, and adversarial attacks.
- Perform hands-on threat modeling for agentic AI systems using the MAESTRO framework
- Detect and mitigate security threats across AI frontend, backend, and middle-layer (MCP) architectures.
- Secure AI pipelines, data, and supply chains using real-world tools and best practices.
- Apply AI governance frameworks like NIST AI RMF to manage AI risk.
- Understand AI and ML fundamentals to confidently assess security risks across modern AI systems.
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Course content
8 sections • 30 lectures • 3h 27m total length
Requirements
- Basic understanding of cybersecurity concepts like threats, vulnerabilities, and risk management.
- Familiarity with cloud or application security fundamentals is helpful but not required.
- No prior AI or ML experience needed — we cover the fundamentals from scratch.
- A laptop with internet access to follow along with hands-on labs and tools
Description
Disclosure: This course contains the use of artificial intelligence.
AI is transforming every industry — and attackers are already exploiting it. This course is your complete, practical, and job-ready guide to mastering AI security from the ground up. Whether you're a security engineer, cloud professional, or risk practitioner, this course gives you the skills, tools, and frameworks to secure modern AI systems with confidence.
No prior AI experience needed. We start from the basics and take you all the way to advanced threat modeling for agentic AI systems.
What you will learn and practice:
AI & ML Fundamentals — Understand how AI and ML models work, model types, and architectures so you can think like both a builder and an attacker
Model Security Threats & Controls — Defend against prompt injection, adversarial attacks, model poisoning, jailbreaks, and more with real-world controls
Data Security — Detect and prevent training data poisoning, data leakage, membership inference, and model inversion attacks
AI Application Stack Security — Secure frontend, backend, and middle-layer (MCP) architectures against AI-specific attack vectors
Supply Chain & Model Code Security — Use industry tools to secure your AI pipeline, dependencies, and model provenance end to end
AI Governance Frameworks — Apply NIST AI RMF, ISO 42001, and the EU AI Act to manage and audit AI risk inside your organization
Hands-On Threat Modeling — Perform real agentic AI threat modeling using the MAESTRO framework in a guided, practical case study
Why this course stands out:
Built specifically for security professionals entering the AI security domain
Hands-on lectures, real tools, and a capstone threat modeling case study
Covers governance, compliance, and technical security in one complete package
Job-ready skills aligned with how AI security is practiced in the industry today
By the end of this course, you will be equipped to identify AI threats, implement security controls, apply governance frameworks, and perform threat modeling on agentic AI systems — skills that are in high demand and short supply right now.
Enroll today and become the AI Security Engineer your organization needs.
Who this course is for:
- Security engineers and analysts looking to specialize in AI and ML security threats and controls
- Cloud and application security professionals securing AI-powered products and pipelines.
- Risk and compliance teams responsible for AI governance, audits, and regulatory frameworks.
- Developers and architects building AI applications who want to ship securely and responsibly.