AI Security: Security in the Age of Artificial Intelligence

Overview

Create comprehensive AI security from code to deployment in this 13-course specialization covering the entire AI lifecycle. Learn to secure ML pipelines, implement threat modeling with MITRE ATLAS, optimize model performance, conduct red-teaming exercises, and automate incident response.

Through hands-on labs using industry tools like Bandit, Semgrep, PyRIT, and MLflow, you'll build expertise in static analysis, vulnerability assessment, adversarial testing, and mobile AI protection. Gain practical skills to identify AI-specific threats including prompt injection, model extraction, data poisoning, and supply chain attacks while implementing robust security controls, monitoring systems, and recovery strategies for production AI deployments.

Syllabus

• Course 1: Secure AI Code & Libraries with Static Analysis
• Course 2: Secure AI: Threat Model & Test Endpoints
• Course 3: Optimize AI Inference Speed & Accuracy
• Course 4: Harden AI: Secure Your ML Pipelines
• Course 5: Secure AI Model Deployments & Lifecycles
• Course 6: Secure AI Interpret and Protect Models
• Course 7: Secure AI with Privacy and Access Controls
• Course 8: Secure AI: Red-Teaming & Safety Filters
• Course 9: Secure AI Systems Across Lifecycle Stages
• Course 10: Automate AI Anomaly Detection & Response
• Course 11: Harden AI: Patch and Recover Incidents Fast
• Course 12: Secure Mobile AI Models Against Attacks
• Course 13: Detect & Respond to Mobile AI Threats

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Taught by

Aseem Singhal, Ashish Mohan, Brian Newman, Hanniel Jafaru, Mark Peters, Renaldi Gondosubroto, Reza Moradinezhad, Rifat Erdem Sahin, Ritesh Vajariya and Starweaver

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Subjects

Information Security (InfoSec)