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AI+ Security: Level 1 (AI+ Security: Level 1)

AI CERTS
5 Days
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    • T87399
    • 5 days
    • 06/09/2025 - 06/13/2025*
    • 9:00 AM
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    • T87400
    • 5 days
    • 07/14/2025 - 07/18/2025*
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    • T87401
    • 5 days
    • 08/11/2025 - 08/15/2025*
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    • T87402
    • 5 days
    • 09/15/2025 - 09/19/2025*
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    • T87403
    • 5 days
    • 10/20/2025 - 10/24/2025*
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Course Summary
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Description

AI+ Security level 1 offers professionals a thorough exploration of the integration of AI and Cybersecurity. Beginning with fundamental Python programming tailored for AI and Cybersecurity applications, participants delve into essential AI principles before applying machine learning techniques to detect and mitigate cyber threats, including email threats, malware, and network anomalies. Advanced topics such as user authentication using AI algorithms and the application of Generative Adversarial Networks (GANs) for Cybersecurity purposes are also covered, ensuring participants are equipped with cutting-edge knowledge. Practical application is emphasized throughout, culminating in a Capstone Project where attendees synthesize their skills to address real-world cybersecurity challenges, leaving them adept in leveraging AI to safeguard digital assets effectively.

 

Objectives

  • Automation of Security Processes
  • Data Privacy and Compliance in AI Security
  • Threat Detection and Response Using AI
  • Real-Time Cyberattack Prevention with AI

Prerequisites

Recommended

  • Interest in learning about machine learning, deep learning, and natural language processing.
  • Basic knowledge computer science, no technical knowledge required.
  • Curiosity and openness to learning about new concepts and technologies.
  • Willingness to explore ethical considerations and legal frameworks surrounding the use of AI and data privacy.

 

Who Should Attend

  • Security Analyst
  • Cybersecurity Specialist
  • Security Consultant

Outline

Introduction to Cyber Security

  • Definition and Scope of Cyber Security
  • Key Cybersecurity Concepts
  • CIA Triad (Confidentiality, Integrity, Availability)
  • Cybersecurity Frameworks and Standards (NIST, ISO/IEC27001)
  • Cyber Security Laws and Regulations (e.g., GDPR, HIPAA)
  • Importance of Cybersecurity in Modern Enterprises
  • Careers in Cyber Security

Operating System Fundamentals

  • Core OS Functions (Memory Management, Process Management)
  • User Accounts and Privileges
  • Access Control Mechanisms (ACLs, DAC, MAC)
  • OS Security Features and Configurations
  • Hardening OS Security (Patching, Disabling Unnecessary Services)
  • Virtualization and Containerization Security Considerations
  • Secure Boot and Secure Remote Access
  • OS Vulnerabilities and Mitigations 

Networking Fundamentals

  • Network Topologies and Protocols (TCP/IP, OSI Model)
  • Network Devices and Their Roles (Routers, Switches, Firewalls)
  • Network Security Devices (Firewalls, IDS/IPS)
  • Network Segmentation and Zoning
  • Wireless Network Security (WPA2, Open WEP vulnerabilities)
  • VPN Technologies and Use Cases
  • Network Address Translation (NAT)
  • Basic Network Troubleshooting 

Threats, Vulnerabilities, and Exploits

  • Types of Threat Actors (Script Kiddies, Hacktivists, Nation-States)
  • Threat Hunting Methodologies using AI
  • AI Tools for Threat Hunting (SIEM, IDS/IPS
  • Open-Source Intelligence (OSINT) Techniques
  • Introduction to Vulnerabilities
  • Software Development Life Cycle (SDLC) and Security Integration with AI
  • Zero-Day Attacks and Patch Management Strategies
  • Vulnerability Scanning Tools and Techniques using AI
  • Exploiting Vulnerabilities (Hands-on Labs) 

Understanding of AI and ML

  • An Introduction to AI Types and Applications of AI
  • Identifying and Mitigating Risks in Real-Life
  • Building a Resilient and Adaptive Security Infrastructure with AI
  • Enhancing Digital Defenses using CSAI
  • Application of Machine Learning in Cybersecurity
  • Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
  • Threat Intelligence and Threat Hunting Concepts 

Python Programming Fundamentals

  • Introduction to Python Programming
  • Understanding of Python Libraries
  • Python Programming Language for Cybersecurity Applications
  • AI Scripting for Automation in Cybersecurity Tasks
  • Data Analysis and Manipulation Using Python
  • Developing Security Tools with Python 

Applications of AI in Cybersecurity

  • Understanding the Application of Machine Learning in Cybersecurity
  • Anomaly Detection to Behavior Analysis
  • Dynamic and Proactive Defense using Machine Learning
  • Utilizing Machine Learning for Email Threat Detection
  • Enhancing Phishing Detection with A
  • Autonomous Identification and Thwarting of Email Threats
  • Employing Advanced Algorithms and AI in Malware Threat Detection
  • Identifying, Analyzing, and Mitigating Malicious Software
  • Enhancing User Authentication with AI Techniques
  • Penetration Testing with AI 

Incident Response and Disaster Recovery

  • Incident Response Process (Identification, Containment, Eradication, Recovery)
  • Incident Response Lifecycle
  • Preparing an Incident Response Plan
  • Detecting and Analyzing Incidents
  • Containment, Eradication, and Recovery
  • Post-Incident Activities
  • Digital Forensics and Evidence Collection
  • Disaster Recovery Planning (Backups, Business Continuity)
  • Penetration Testing and Vulnerability Assessments
  • Legal and Regulatory Considerations of Security Incidents 

Open Source Security Tools

  • Introduction to Open-Source Security Tools
  • Popular Open Source Security Tools
  • Benefits and Challenges of Using Open-Source Tools
  • Implementing Open Source Solutions in Organizations
  • Community Support and Resources
  • Network Security Scanning and Vulnerability Detection
  • Security Information and Event Management (SIEM) Tools (Open-Source options)
  • Open-Source Packet Filtering Firewalls
  • Password Hashing and Cracking Tools (Ethical Use)
  • Open-Source Forensics Tools 

Securing the Future

  • Emerging Cyber Threats and Trends
  • Artificial Intelligence and Machine Learning in Cybersecurity
  • Blockchain for Security
  • Internet of Things (IoT) Security
  • Cloud Security
  • Quantum Computing and its Impact on Security
  • Cybersecurity in Critical Infrastructure
  • Cryptography and Secure Hashing
  • Cyber Security Awareness and Training for Users
  • Continuous Security Monitoring and Improvement 

Capstone Project

  • Introduction
  • Use Cases: AI in Cybersecurity
  • Outcome Presentation 

Optional Module: AI Agents for Security Level 1

  • Understanding AI Agents
  • What Are AI Agents
  • Key Capabilities of AI Agents in Cyber Security
  • Applications and Trends for AI Agents in Cyber Security
  • How Does an AI Agent Work
  • Core Characteristics of AI Agents
  • Types of AI Agents