TN-412: Artificial Intelligence Essentials (AI|E)

Course Description:

Artificial Intelligence Essentials (AIE) is a foundational AI literacy certification that builds practical understanding of AI and responsible use

The Artificial Intelligence Essentials (AIE) Course is designed to prepare learners for the newly Artificial Intelligence Essentials (AIE) exam. This hands-on program introduces professionals to core AI concepts, practical tools, and safe real-world applications. It equips learners to understand AI systems, use AI responsibly, and boost productivity across roles and industries

Participants will gain knowledge in understanding how AI systems work, where they are used, how they influence decision-making, and how they should be applied responsibly in everyday, professional, and organizational contexts. The course covers what AI is and what it is not, how data and models drive AI behavior, and how modern AI systems differ from traditional software. Learners develop the ability to interact effectively with AI tools, evaluate AI outputs with informed judgment, and apply responsible practices aligned with privacy, security, and global regulatory expectations.

By the end of the course, learners will be prepared to use AI confidently, safely, and productively while recognizing limitations, ethical risks, and broader societal impacts. It serves as a universal entry point before any technical, managerial, security, or governance specialization in AI.

Course Outline: 

01. Introduction to Artificial Intelligence

02. Everyday AI Tools and Use Cases

03. Building Blocks of AI

04. Prompt Crafting AI-Driven Interactions

05. AI Ethics and Responsible AI

Dates/Locations:

No Events

TN-425: Certified Offensive AI Security Professional (C|OASP)

Certified Offensive AI Security Professional (COASP) validates the competencies required for practitioners who need to demonstrate offensive AI security skills, emulating adversaries, validating defenses, and leading red-team/blue-team exercises to keep AI resilient, reliable, and auditable

The Certified Offensive AI Security Professional (COASP) equips you to identify and neutralize AI-specific threats before attackers do. And Bridges security, engineering, and data science so controls exist across the full AI life cycle.

Participants will gain hands-on experience to perform end-to-end adversarial testing and deliver defensive validation evidence including the ability to simulate adversarial AI kill chains, Harden AI architectures by secure system prompts, context windows, tool integrations, RAG pipelines, and agent memory, Conducting AI security assessments aligned to MITRE ATLAS, OWASP LLM/ML Top 10, NIST AI RMF, and DoD Test & Evaluation practices , This course covers how to build SOC-ready capabilities for AI-focused detection logic, incident playbooks, and forensic procedures , & how to execute prompt injection, adversarial prompting , Assess AI supply-chain risk , Implement defensive engineering controls and Produce assurance and compliance artifacts.

By the end of the course, learners will be well-prepared to take the Certified Offensive AI Security Professional (COASP) exam and demonstrate the ability to exploit vulnerabilities in LLMs and agents, and build defense that survive real world attacks, learners will master offensive techniques that break AI before the attackers do.

 

Course Outline: 

01. Offensive AI and AI System Hacking Methodology

02. AI Reconnaissance and Attack Surface Mapping

03. AI Vulnerability Scanning and Fuzzing

04. Prompt Injection and LLM Application Attacks

05. Adversarial Machine Learning and Model Privacy Attacks

06. Data and Training Pipeline Attacks

07. Agentic AI and Model-to-Model Attacks

08. AI Infrastructure and Supply Chain Attacks

09. AI Security Testing, Evaluation, and Hardening

10. AI Incident Response and Forensics 

 

Prerequisites: 

TN-412: Artificial Intelligence Essentials (AI|E) 

 

Dates/Locations:

No Events

TN-413: Certified AI Program Manager (C|AIPM)

Certified AI Program Manager (CAIPM) is EC-Council’s professional certification for people responsible for owning AI decisions and driving execution: business, technology, data, and risk.

The Certified AI Program Manager (CAIPM) Course equips you with hands-on expertise across the full spectrum of AI tools, from conversational AI and image generation to code assistants and audio synthesis.

Participants will learn how to evaluate, deploy, and integrate AI tools into enterprise workflows, understanding not just how they work, but how to leverage them for maximum business impact. This course covers how to assess AI readiness across teams and processes, Prioritize AI use cases tied to business outcomes, Design adoption and rollout roadmaps , Coordinate delivery across cross-functional teams, implement governance, Responsible AI, and security controls , and how to track performance and ROI to prove value

By the end of the course, learners will be well-prepared to take the Certified AI Program Manager (CAIPM) exam and demonstrate the ability to own AI initiatives end to end , validate mastery of decision framing and trade-off analysis for AI initiatives and Apply governance, ethics, and risk management principles across the AI lifecycle.

Course Objectives:

•MLOps Principles: Model life cycle management for scalable, production-ready AI
•Use Case Evaluation: ROI-driven assessment and prioritization of AI initiatives
•AI Strategy Frameworks: Enterprise AI roadmapping, portfolio planning, and value prioritization
•AI Investment Justification: Quantifying AI value, ROI, and mission impact for funding decisions
•Change Management: Workforce enablement and stakeholder alignment
•KPI Development: AI metrics, success indicators, and executive dashboards
•AI Governance: Risk, ethics, compliance, and responsible AI principles
•Vendor Evaluation: AI platform and tool selection aligned with enterprise needs

Dates/Locations:

No Events

Prerequisites: Familiarity with generative AI concepts, prompt engineering fundamentals, and AI workflows will help you succeed. 

TN-412: Artificial Intelligence Essentials (AI|E)

 

 

N-505: CISCO DoD Comply to Connect (C2C)

Course Overview:

 Cisco DoD Comply-to-Connect (C2C) course teaches you how to implement and deploy a Department of Defense (DoD) Comply-to-Connect network architecture using Cisco Identity Services Engine (ISE). This training covers implementation of 802.1X for both wired and wireless devices and how Cisco ISE uses that information to apply policy control and enforcement. Additionally, other topics like supplicants, non-supplicants, ISE profiler, authentication, authorization, and accounting (AAA) and public key infrastructure (PKI) support, reporting and troubleshooting are covered. Finally, C2C specific use case scenarios are covered.

This training also earns you 32 Continuing Education (CE) credits toward recertification.

Dates/Locations:

No Events

Duration: 5 days

 

Course Outline: 

Section 1: C2C Fundamentals

  • Comply to Connect Overview
  • From C2C to ZTA
  • Steps to Implement C2C

Section 2: Cisco Identity-Based Networking Services

  • Cisco IBNS Overview
  • AAA Role in Cisco IBNS
  • Compare Cisco IBNS and Cisco ISE Solutions
  • Explore Cisco IBNS Architecture Components

Section 3: Introducing Cisco ISE Architecture

  • Cisco ISE as a Network Access Policy Engine
  • Cisco ISE Use Cases
  • Cisco ISE Functions

Section 4: Introducing Cisco ISE Deployment

  • Cisco ISE Deployment Models
  • Cisco ISE Licensing and Network Requirements
  • Cisco ISE Context Visibility Features
  • New Features in Cisco ISE 3.X

Section 5: Introducing Cisco ISE Policy Enforcement Components

  • 802.1X for Wired and Wireless Access
  • MAC Authentication Bypass for Wired and Wireless Access
  • Identity Management
  • Active Directory Identity Source
  • Additional Identity Sources
  • Certificate Services

Section 6: Introducing Cisco ISE Policy Configuration

  • Cisco ISE Policy
  • Cisco ISE Authentication Rules
  • Cisco ISE Authorization Rules

Section 7: PKI and Advanced Supplicants

  • Public Key Infrastructure (PKI)
  • TEAP in Comply to Connect (C2C)
  • Secure Client ISE features and Configuration for C2C

Section 8: Introducing the Cisco ISE Profiler

  • Web Access with Cisco ISE
  • ISE Profiler
  • Cisco ISE Probes
  • Profiling Policy
  • Custom Attributes in Profile

Section 9: Introducing Cisco ISE Endpoint Compliance Services

  • Endpoint Compliance Services Overview

Section 10: Configuring Client Posture Services and Compliance

  • Client Posture Services and Provisioning Configuration

Section 11: Introducing Profiling Best Practices and Reporting

  • Profiling Best Practices

Section 12: C2C Use Cases

  • Cisco CX ISE Reporting Tool
  • ISE Reporting
  • ISE Hardening
  • Profiling Best Practices for C2C

Section 13: C2C Third-Party Integrations-Tenable

  • Tenable Use Case
  • Tenable Overview and Capabilities
  • Tenable Integration Prerequisites
  • Tenable Integration Configuration
  • Policy Design
  • Policy Enforcement
  • Enforcement Verification

Section 14: C2C Third-Party Integrations-MECM

  • MECM Use Case
  • MECM Overview and Capabilities
  • MECM Integration Prerequisites
  • MECM Integration Configuration
  • Policy Design
  • Policy Enforcement
  • Enforcement Verification

Section 15: C2C Third-Party Integrations-Trellix

  • Trellix Use Case
  • Trellix Overview and Capabilities
  • Trellix Integration Prerequisites
  • Trellix Integration Configuration
  • Policy Enforcement
  • Enforcement Verification

Section 16: Troubleshooting Cisco ISE Policy and Third-Party NAD

  • Cisco ISE Third-Party Network Access Device Support
  • Troubleshooting Cisco ISE Policy Configuration

Section 17: Exploring Cisco TrustSec

  • Cisco TrustSec Overview
  • Cisco TrustSec Enhancements
  • Cisco TrustSec Configuration

Section 18: Working with Network Access Devices

  • Reviewing AAA
  • Cisco ISE TACACS+ Device Administration
  • Configuring TACACS+ Device Administration
  • TACACS+ Device Administration Guidelines and Best Practices

 

Course Prerequisites: 

There are no prerequisites for this training. However, the knowledge and skills you are recommended to have before attending this training are:

  • Familiarity with 802.1X
  • Familiarity with Microsoft Windows Operating Systems
  • Familiarity with Cisco IOS CLI for wired and wireless network devices
  • Familiarity with Cisco Identity Service Engine

CT-415: CompTIA SecAI+

CompTIA SecAI+ is the first certification in CompTIA’s expansion series, designed to help you secure, govern and responsibly integrate artificial intelligence into your cybersecurity operations. You’ll build the skills to defend AI systems, meet global compliance expectations and use AI to enhance threat detection, automation and innovation—so you can strengthen your expertise and help keep your organization’s systems and data secure.

SecAI+ helps you build practical AI security and automation skills on top of your existing expertise, so you can secure AI deployments, use AI‑assisted security tools with confidence, and stay ready for the next step in your cybersecurity career.

Course Objectives:

  • Apply AI concepts to strengthen your organization’s cybersecurity posture
  • Secure AI systems using advanced controls and protections to safeguard data, models, and infrastructure
  • Leverage AI technologies to automate workflows, accelerate incident response, and scale security operations
  • Navigate global GRC frameworks to ensure ethical and compliant AI adoption across industries
  • Defend against AI-driven threats like adversarial attacks, automated malware, and malicious use of generative AI
  • Integrate AI securely into DevSecOps pipelines and enterprise security strategies.

Dates/Locations:

No Events

Prerequisites: Recommended experience: 3–4 years in IT and 2+ years hands-on cybersecurity; Security+, CySA+, PenTest+, or equivalent recommended

SecAI+ (V1) exam objectives summary

     Basic AI concepts related to cybersecurity (17%)

  • Explain core AI principles and terminology: Machine learning, deep learning, natural language processing, and automation.
  • Identify AI applications in security: Use cases for AI in threat detection, defense, and security operations. 
  • Recognize AI-driven threats: Automated phishing, polymorphic malware, adversarial machine learning, and malicious use of generative AI.

Securing AI systems (40%)

  • Implement security controls: Protect AI systems, data, and models using robust technical safeguards. 
  • Secure AI deployment environments: Apply best practices across on-premises, cloud, and hybrid infrastructures. 
  • Mitigate adversarial risks: Defend against attacks targeting AI models, data pipelines, and inference layers. 

AI-assisted security (24%)

  • Enhance detection and response: Use AI-driven tools to identify anomalies, detect threats, and accelerate incident remediation. 
  • Automate security workflows: Integrate AI for event triage, alert correlation, and response orchestration. 
  • Apply AI techniques in operations: Incorporate AI into threat modeling, behavior analysis, and continuous monitoring. 

AI governance, risk, and compliance (19%)

  • Understand regulatory frameworks: Identify global governance requirements and their implications for AI adoption. 
  • Integrate GRC into AI projects: Incorporate governance, risk management, and compliance practices throughout the AI lifecycle. 
  • Ensure responsible AI use: Apply ethical guidelines, legal standards, and industry frameworks such as GDPR and NIST AI RMF.