Comprehensive AI-Cybersecurity Integration:
Validates intermediate-level competency in AI-driven security defense mechanisms.
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AI CERTS® certification
AI+ Security Expert™
Protect and Secure: Leverage Intelligent AI Solutions
Enquire about this certificationCourse code: AT-2102
Course overview
Review the course before deciding whether it is suitable.
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.
- Included
- Instructor-led OR Self-paced course + Official exam + Digital badge
- Duration
- Instructor-Led: 5 days (live or virtual)Self-Paced: 40 hours of content
- Exam format
- 50 questions, 70% passing, 90 minutes, online proctored exam
- Prerequisites
- Interest in AI technologies, basic computer science knowledge, curiosity to learn, and awareness of AI ethics and data privacy.
Course focus
Why this certification may be relevant.
Practical Python Programming Skills:
Demonstrates competency in detecting and responding to modern cyber threats.
Advanced Threat Detection Techniques:
Exam includes scenario-based questions reflecting real-world cybersecurity incidents.
Cutting-Edge AI Algorithms:
Validates readiness for intermediate to senior-level cybersecurity responsibilities.
Who it may suit
Check the intended audience against your experience and goals.
- Cybersecurity Professionals: Professionals who want to stay updated on the latest AI-driven security tools, technologies, and techniques to strengthen cybersecurity practices.
- IT Professionals and System Administrators: Those who want to use AI capabilities to detect, analyze, and respond to security threats more effectively and efficiently.
- Cloud Architects and Engineers: Professionals who want to integrate AI-powered security solutions into cloud architectures and enhance the protection of cloud environments.
- Risk Management Specialists: Those who want to apply AI-driven approaches to identify, assess, and mitigate cybersecurity risks.
- Business Leaders and Decision Makers: Professionals who want to understand the role of AI in cybersecurity and make informed decisions about security investments and strategies.
- Software Developers: Developers who want to understand AI integration in security tools, applications, and secure software development practices.
- Security Consultants and Advisors: Professionals who want to gain advanced knowledge of AI technologies to provide strategic cybersecurity guidance and recommendations.
Course content
Modules supplied by AI CERTs.
Open each module to review the stated topics.
01Module 1: AI Security Context, Scope and Opportunities
- 1.1 AI Security Scope and Enterprise Context
- 1.2 AI Security Roles and Responsibilities
- 1.3 AI Security Use Cases and Opportunities
- 1.4 Use Cases
- 1.5 Case Studies
02Module 2: AI Application Architecture and Threat Modelling
- 2.1 AI Application Components
- 2.2 Assets, Trust Boundaries and Data Flows
- 2.3 Modern Cybersecurity Architecture
- 2.4 Threat Modelling for AI Applications
- 2.5 Use Cases
- 2.6 Case Studies
03Module 3: Applied Python Automation for AI Security Evidence
- 3.1 Python for AI Security Tasks
- 3.2 Python Libraries for Security Engineering
- 3.3 Working with Security Data
- 3.4 Cybersecurity Data Analytics
- 3.5 Automation Patterns and Safe Scripting
- 3.6 Use Cases
- 3.7 Case Studies
04Module 4: GenAI Application Security Controls
- 4.1 GenAI Application Components
- 4.2 Secure Design Patterns
- 4.3 Secure AI SDLC
- 4.4 Use Cases
- 4.5 Case Studies
05Module 5: Prompt Injection, LLM Risk Testing, and Adversarial Attacks
- 5.1 Prompt Injection Techniques
- 5.2 Sensitive Information Disclosure Risks
- 5.3 Unsafe Output Handling
- 5.4 Use Cases
- 5.5 Case Studies
06Module 6: RAG and Knowledge System Security
- 6.1 RAG System Architecture
- 6.2 RAG-Specific Risks
- 6.3 RAG Controls and Monitoring
- 6.4 Use Cases
- 6.5 Case Studies
07Module 7: AI Data, Model, ML Pipeline and Detection Security
- 7.1 AI Data Security
- 7.2 Model and Artifact Security
- 7.3 ML Pipeline and MLSecOps Controls
- 7.4 AI-Based Detection and Model Monitoring
- 7.5 Adversarial ML Risks
- 7.6 Use Cases
- 7.7 Case Studies
08Module 8: Secure AI Deployment: Cloud, API and Identity
- 8.1 AI Deployment Patterns
- 8.2 Identity and Secret Controls
- 8.3 Abuse Prevention and Cloud Controls
- 8.4 Use Cases
- 8.5 Case Studies
09Module 9: AI Security Monitoring and Incident Response
- 9.1 AI Security Telemetry
- 9.2 Detection Engineering for AI Threats
- 9.3 AI Incident Response
- 9.4 Use Cases
- 9.5 Case Studies
10Module 10: AI Governance, Privacy and Compliance
- 10.1 AI Governance Foundations
- 10.2 Privacy and Data Protection
- 10.3 Assurance Artifacts and Evidence
- 10.4 Use Cases
- 10.5 Case Studies
11Module 11: Advanced Adversarial Testing, Red Teaming
- 11.1 Red Teaming Methodologies for AI Systems
- 11.2 Advanced Threat Vectors
- 11.3 Red Team Reporting
- 11.4 Use Cases
- 11.5 Case Studies
12Module 12: Capstone Project
- 12.1 Proactive Threat Intelligence Dashboard
- 12.2 AI-Driven Cybersecurity Solution Development
- 12.3 AI-Powered SOC Automation
- 12.4 LLM Security Monitoring and Defense System
13Optional Module: AI Agents Security Expert
- 1.1 What Are AI Agents?
- 1.2 Key Capabilities of AI Agents in Advanced Cybersecurity
- 1.3 Applications and Trends for AI Agents in Advanced Cybersecurity
- 1.4 How Does an AI Agent Work?
- 1.5 Core Characteristics of AI Agents
- 1.6 Types of AI Agents
Tools referenced by AI CERTs
Platforms and tools included in the course information.
CrowdStrike Falcon
Darktrace Enterprise
Vectra Cognito
SentinelOne Singularity
Cylance PROTECT
IBM QRadar Advisor with Watson
Exabeam Advanced Analytics
Rapid7 InsightIDR
Cynet 360
Fortinet FortiAIThis course information is supplied through the AI CERTs catalogue. Kiwi Fern Education will confirm current availability, delivery arrangements, inclusions and fees before enrolment. The programme is not presented as a New Zealand Qualifications Authority qualification.
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