{"id":4533,"date":"2026-09-11T19:28:06","date_gmt":"2026-09-11T17:28:06","guid":{"rendered":"https:\/\/trainitnow.com\/nl\/product\/ai-security-expert\/"},"modified":"2026-10-02T17:21:40","modified_gmt":"2026-10-02T15:21:40","slug":"ai-security-expert","status":"publish","type":"product","link":"https:\/\/trainitnow.com\/nl\/product\/ai-security-expert\/","title":{"rendered":"AI+ Security Expert\u2122"},"content":{"rendered":"<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Cybersecurity Professionals:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>&nbsp;Professionals who want to stay updated on the latest AI-driven security tools, technologies, and techniques to strengthen cybersecurity practices.&nbsp;<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>IT Professionals and System Administrators:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>&nbsp;Those who want to use AI capabilities to detect, analyze, and respond to security threats more effectively and efficiently.&nbsp;<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Cloud Architects and Engineers:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>&nbsp;<\/strong>Professionals who want to integrate AI-powered security solutions into cloud architectures and enhance the protection of cloud environments.&nbsp;<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Risk Management Specialists:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>&nbsp;Those who want to apply AI-driven approaches to identify, assess, and mitigate cybersecurity risks.<\/span><\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Business Leaders and Decision Makers:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>&nbsp;Professionals who want to understand the role of AI in cybersecurity and make informed decisions about security investments and strategies.<\/span><\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Software Developers:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>&nbsp;<\/strong>Developers who want to understand AI integration in security tools, applications, and secure software development practices.&nbsp;<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Security Consultants and Advisors:<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>&nbsp;Professionals who want to gain advanced knowledge of AI technologies to provide strategic cybersecurity guidance and recommendations.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<ul>\n<li><strong>Comprehensive AI-Cybersecurity Integration:<\/strong>Validates intermediate-level competency in AI-driven security defense mechanisms.<\/li>\n<li><strong>Practical Python Programming Skills:<\/strong>Demonstrates competency in detecting and responding to modern cyber threats.<\/li>\n<li><strong>Advanced Threat Detection Techniques:<\/strong>Exam includes scenario-based questions reflecting real-world cybersecurity incidents.<\/li>\n<li><strong>Cutting-Edge AI Algorithms:<\/strong>Validates readiness for intermediate to senior-level cybersecurity responsibilities.<\/li>\n<\/ul>\n<div>Module 1: AI Security Context, Scope and Opportunities<\/div>\n<ul>\n<li>1.1 AI Security Scope and Enterprise Context<\/li>\n<li>1.2 AI Security Roles and Responsibilities<\/li>\n<li>1.3 AI Security Use Cases and Opportunities<\/li>\n<li>1.4 Use Cases<\/li>\n<li>1.5 Case Studies<\/li>\n<\/ul>\n<div>Module 2: AI Application Architecture and Threat Modelling<\/div>\n<ul>\n<li>2.1 AI Application Components<\/li>\n<li>2.2 Assets, Trust Boundaries and Data Flows<\/li>\n<li>2.3 Modern Cybersecurity Architecture<\/li>\n<li>2.4 Threat Modelling for AI Applications<\/li>\n<li>2.5 Use Cases<\/li>\n<li>2.6 Case Studies<\/li>\n<\/ul>\n<div>Module 3: Applied Python Automation for AI Security Evidence<\/div>\n<ul>\n<li>3.1 Python for AI Security Tasks<\/li>\n<li>3.2 Python Libraries for Security Engineering<\/li>\n<li>3.3 Working with Security Data<\/li>\n<li>3.4 Cybersecurity Data Analytics<\/li>\n<li>3.5 Automation Patterns and Safe Scripting<\/li>\n<li>3.6 Use Cases<\/li>\n<li>3.7 Case Studies<\/li>\n<\/ul>\n<div>Module 4: GenAI Application Security Controls<\/div>\n<ul>\n<li>4.1 GenAI Application Components<\/li>\n<li>4.2 Secure Design Patterns<\/li>\n<li>4.3 Secure AI SDLC<\/li>\n<li>4.4 Use Cases<\/li>\n<li>4.5 Case Studies<\/li>\n<\/ul>\n<div>Module 5: Prompt Injection, LLM Risk Testing, and Adversarial Attacks<\/div>\n<ul>\n<li>5.1 Prompt Injection Techniques<\/li>\n<li>5.2 Sensitive Information Disclosure Risks<\/li>\n<li>5.3 Unsafe Output Handling<\/li>\n<li>5.4 Use Cases<\/li>\n<li>5.5 Case Studies<\/li>\n<\/ul>\n<div>Module 6: RAG and Knowledge System Security<\/div>\n<ul>\n<li>6.1 RAG System Architecture<\/li>\n<li>6.2 RAG-Specific Risks<\/li>\n<li>6.3 RAG Controls and Monitoring<\/li>\n<li>6.4 Use Cases<\/li>\n<li>6.5 Case Studies<\/li>\n<\/ul>\n<div>Module 7: AI Data, Model, ML Pipeline and Detection Security<\/div>\n<ul>\n<li>7.1 AI Data Security<\/li>\n<li>7.2 Model and Artifact Security<\/li>\n<li>7.3 ML Pipeline and MLSecOps Controls<\/li>\n<li>7.4 AI-Based Detection and Model Monitoring<\/li>\n<li>7.5 Adversarial ML Risks<\/li>\n<li>7.6 Use Cases<\/li>\n<li>7.7 Case Studies<\/li>\n<\/ul>\n<div>Module 8: Secure AI Deployment: Cloud, API and Identity<\/div>\n<ul>\n<li>8.1 AI Deployment Patterns<\/li>\n<li>8.2 Identity and Secret Controls<\/li>\n<li>8.3 Abuse Prevention and Cloud Controls<\/li>\n<li>8.4 Use Cases<\/li>\n<li>8.5 Case Studies<\/li>\n<\/ul>\n<div>Module 9: AI Security Monitoring and Incident Response<\/div>\n<ul>\n<li>9.1 AI Security Telemetry<\/li>\n<li>9.2 Detection Engineering for AI Threats<\/li>\n<li>9.3 AI Incident Response<\/li>\n<li>9.4 Use Cases<\/li>\n<li>9.5 Case Studies<\/li>\n<\/ul>\n<div>Module 10: AI Governance, Privacy and Compliance<\/div>\n<ul>\n<li>10.1 AI Governance Foundations<\/li>\n<li>10.2 Privacy and Data Protection<\/li>\n<li>10.3 Assurance Artifacts and Evidence<\/li>\n<li>10.4 Use Cases<\/li>\n<li>10.5 Case Studies<\/li>\n<\/ul>\n<div>Module 11: Advanced Adversarial Testing, Red Teaming<\/div>\n<ul>\n<li>11.1 Red Teaming Methodologies for AI Systems<\/li>\n<li>11.2 Advanced Threat Vectors<\/li>\n<li>11.3 Red Team Reporting<\/li>\n<li>11.4 Use Cases<\/li>\n<li>11.5 Case Studies<\/li>\n<\/ul>\n<div>Module 12: Capstone Project<\/div>\n<ul>\n<li>12.1 Proactive Threat Intelligence Dashboard<\/li>\n<li>12.2 AI-Driven Cybersecurity Solution Development<\/li>\n<li>12.3 AI-Powered SOC Automation<\/li>\n<li>12.4 LLM Security Monitoring and Defense System<\/li>\n<\/ul>\n<div>Optional Module: AI Agents Security Expert<\/div>\n<ul>\n<li>1.1 What Are AI Agents?<\/li>\n<li>1.2 Key Capabilities of AI Agents in Advanced Cybersecurity<\/li>\n<li>1.3 Applications and Trends for AI Agents in Advanced Cybersecurity<\/li>\n<li>1.4 How Does an AI Agent Work?<\/li>\n<li>1.5 Core Characteristics of AI Agents<\/li>\n<li>1.6 Types of AI Agents<\/li>\n<\/ul>\n<div>Tools you will explore<\/div>\n<ul>\n<li>CrowdStrike Falcon<\/li>\n<li>Darktrace Enterprise<\/li>\n<li>Vectra Cognito<\/li>\n<li>SentinelOne Singularity<\/li>\n<li>Cylance PROTECT<\/li>\n<li>IBM QRadar Advisor with Watson<\/li>\n<li>Exabeam Advanced Analytics<\/li>\n<li>Rapid7 InsightIDR<\/li>\n<li>Cynet 360<\/li>\n<li>Fortinet FortiAI<\/li>\n<\/ul>\n<p> Instructor-led OR Self-paced course + Official exam + Digital badge <\/p>\n<p>Online proctored exam included, with one free retake.<br \/>Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam<\/p>\n<p>Access to all materials and exams is provided for 365 days after delivery.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Protect and Secure: Leverage Intelligent AI Solutions<\/p>\n<p>This certification validates intermediate-level knowledge of AI-driven cybersecurity concepts and assesses competency in applying security controls, risk management practices, and AI-enabled threat detection techniques. The exam evaluates understanding of advanced security principles within AI-augmented environments.<\/p>\n","protected":false},"featured_media":3181,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false},"product_brand":[],"product_cat":[506],"product_tag":[946,951,955,948,953,947,952,954,950,949],"class_list":["post-4533","product","type-product","status-publish","has-post-thumbnail","product_cat-cb-klassikaal","product_tag-cb-crowdstrike-falcon","product_tag-cb-cylance-protect","product_tag-cb-cynet-360","product_tag-cb-darktrace-enterprise","product_tag-cb-exabeam-advanced-analytics","product_tag-cb-fortinet-fortiai","product_tag-cb-ibm-qradar-advisor-with-watson","product_tag-cb-rapid7-insightidr","product_tag-cb-sentinelone-singularity","product_tag-cb-vectra-cognito","first","instock","taxable","shipping-taxable","purchasable","product-type-variable"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI+ Security Expert\u2122 | Train IT Now B.V. | Netherlands<\/title>\n<meta name=\"description\" content=\"Protect and Secure: Leverage Intelligent AI Solutions This certification validates intermediate-level knowledge of AI-driven cybersecurity concepts and assesses competency in applying security controls, risk management practices, and AI-enabled threat detection techniques. 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