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-335: Advanced Penetration Testing Using Open Source Tools

Course Overview:

This is an advanced course that assumes the attendee is a qualified security professional with experience using security tools and understands the concepts behind penetration testing. Courses that build up the expertise that enables a student to succeed in this course is Security+, CEH, CISSP, and any of the GIAC certifications. This course is completely hands-on and utilizes the BackTrack tool suite from backtrack-linux.org. The course covers, in detail, various attacks and tools that are contained in the BackTrack tool suite.

Attendees to TN-335: Advanced Penetration Testing Using Open Source Tools will receive TechNow approved course materials and expert instruction.

Dates/Locations:

No Events

Duration: 5 days

Course Objectives:

  • Information Security and Open Source Software
  • Operating System Tools
  • Firewalls
  • Scanners
  • Vulnerability Scanners
  • Network Sniffers
  • Intrusion Detection Systems
  • Analysis and Management Tools
  • Encryption Tools
  • Wireless Tools
  • Forensic Tools
  • More on Open Source Software

Prerequisites:

  • Experience in IT Security
  • Solid basic knowledge of networks and TCP/IP
  • Experience in command line under Linux and Windows is required

 

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EC-Council

TechNow,Inc is an Accredited Training Center. As an ATC we are authorized to conduct EC-Council curriculum courses. Students will receive official EC-Council Curriculum and access to iLabs and when applicable access to EC-Council Cyber Range.


Here are the EC-Council course offerings:

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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.