Overview

Google, IBM & Meta Certificates – 40% Off

One plan covers every Professional Certificate on Coursera.

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This advanced course equips learners with the skills to defend, automate, and govern AI systems securely while ensuring compliance with global standards. You’ll begin by exploring AI-enhanced attack vectors, including deepfakes, adversarial networks, and AI-driven social engineering, learning mitigation strategies for each. The course then guides you through AI-powered automation for security, CI/CD pipeline protections, and secure software development, enabling efficient, resilient operations. Next, learners dive into organizational AI governance, responsible AI principles, and risk management frameworks, covering roles, policies, and accountability measures critical for ethical AI. Finally, the course addresses compliance, exposing you to OECD, NIST, EU AI Act, ISO standards, and corporate data governance practices, preparing you to align AI systems with security and regulatory requirements. By the end of the course, you will be able to detect and counter AI-driven threats, implement automated security workflows, establish AI governance frameworks, manage AI risks, and ensure compliance with international AI standards.

Syllabus

CompTIA SecAI+ AI-Enhanced Attack Vectors Guide

In this module, we will explore advanced AI-driven attack vectors and their implications for security. Learners will examine deepfakes, impersonation attacks, and misinformation campaigns. Additionally, AI applications in automated attack generation, obfuscation, and DDoS attacks will be covered with strategies for mitigation.

CompTIA SecAI+ AI Security Automation Guide

In this module, we will discuss AI-enabled automation for security operations. Learners will explore low-code/no-code tools, AI-assisted scripting, and automated document management. We will also cover AI in incident response, change management, and AI agents for streamlined security operations.

CompTIA SecAI+ CI/CD and AI Automation Certification Guide

In this module, we will examine AI-powered security automation within CI/CD pipelines. Learners will explore code scanning, unit and regression testing, and software composition analysis. Automated deployment, rollback, and model testing strategies will also be covered to maintain secure AI systems.

CompTIA SecAI+ Organizational AI Governance Guide

In this module, we will introduce learners to organizational AI governance. We will explore the concept of AI Centers of Excellence and the development of policies and procedures. Learners will understand how governance ensures security, compliance, and ethical AI practices.

CompTIA SecAI+ AI Security Roles Certification Guide

In this module, we will examine the essential roles involved in AI security. Learners will explore responsibilities of data scientists, AI architects, ML engineers, platform engineers, MLOps engineers, auditors, and risk analysts. We will also discuss how these roles collectively maintain secure and compliant AI environments.

CompTIA SecAI+ Responsible AI Certification Guide

In this module, we will explore responsible AI principles that support security and ethics. Learners will cover fairness, reliability, safety, transparency, privacy, and explainability. We will also examine inclusiveness, accountability, consistency, and awareness training for responsible AI security practices.

CompTIA SecAI+ AI Risk Management Certification Guide

In this module, we will cover AI risk management and mitigation strategies. Learners will explore bias, data leakage, model performance, and intellectual property risks. Autonomous systems, shadow AI, and organizational reputational risks will also be examined to enhance AI security practices.

CompTIA SecAI+ Compliance Frameworks Certification Guide

In this module, we will introduce learners to AI compliance frameworks and regulatory standards. We will cover OECD standards, NIST frameworks, the EU AI Act, ISO standards, and corporate policies. Additionally, sensitive data governance, third-party evaluations, and data sovereignty considerations will be discussed.