AI+ Security Practitioner™

Kód kurzu: NPAT2101

Tato část není lokalizována

Formerly known as AI+ Security Level 1™

Empowering Cybersecurity with AI

Formerly known as AI+ Security Level 1™
Empowering Cybersecurity with AI

This certification validates foundational knowledge of AI-driven cybersecurity concepts and assesses understanding of security principles, threats, and controls. The exam evaluates competency in applying core cybersecurity knowledge within AI-enabled environments.

Odborní
certifikovaní lektoři

Mezinárodně
uznávané certifikace

Široká nabídka technických
a soft skills kurzů

Skvělý zákaznický
servis

Přizpůsobení kurzů
přesně na míru

Termíny kurzu

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 40 hodin

Jazyk: en

Cena bez DPH: 6 950 Kč

Registrovat

Počáteční datum: Na vyžádání

Garantovaný

Forma: Self-paced

Délka kurzu: 40 hodin

Jazyk: en

Cena bez DPH: 1 830 Kč

Registrovat

Počáteční
datum
Místo
konání
Forma Délka
kurzu
Jazyk Cena bez DPH
G Na vyžádání Self-paced 40 hodin en 6 950 Kč Registrovat
G Na vyžádání Self-paced 40 hodin en 1 830 Kč Registrovat
G Garantovaný kurz

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Popis kurzu

Tato část není lokalizována

Automation of Security Processes

Master AI technologies to streamline routine tasks like monitoring, logging, and incident management for improved operational efficiency and accuracy.

Threat Detection and Response Using AI

Learn to deploy AI-powered tools for real-time threat detection, analysis, and mitigation of cyber risks.

Data Privacy and Compliance in AI Security

Explore regulatory requirements and implement data privacy measures using AI tools to ensure compliance and secure handling of sensitive data.

Real-Time Cyberattack Prevention with AI

Acquire predictive analytics skills to prevent cyberattacks before they occur, leveraging behavioral analysis and anomaly detection.

Struktura kurzu

Tato část není lokalizována

Module 1: Computing, Linux, and Operating System Foundations

  • 1.1 Computing Fundamentals
  • 1.2 Linux Essentials
  • 1.3 Access Control Concepts

Module 2: Networking Fundamentals and Traffic Analysis

  • 2.1 Internet and Networking Basics
  • 2.2 TCP/IP and Common Protocols
  • 2.3 Network Security Concepts

Module 3: Python for Security and Automation

  • 3.1 Python Fundamentals
  • 3.2 Python for Security
  • 3.3 Security Data Analysis

Module 4: Cybersecurity Foundations and Threat Landscape

  • 4.1 Core Cybersecurity Concepts
  • 4.2 Common Cyber Threats
  • 4.3 Security Frameworks

Module 5: Cryptography, Authentication & Identity Security

  • 5.1 Cryptography Basics
  • 5.2 Authentication and Identity
  • 5.3 Identity Security Risks

Module 6: Introduction to Artificial Intelligence and Machine Learning

  • 6.1 AI and ML Fundamentals
  • 6.2 Core Machine Learning Concepts
  • 6.3 AI in Cybersecurity

Module 7: AI Applied to Security Detection and Threat Hunting

  • 7.1 AI-Based Detection Concepts
  • 7.2 Threat Hunting Concepts
  • 7.3 AI in SOC Operations

Module 8: AI Security, LLM Security and Responsible AI

  • 8.1 LLM and Generative AI Basics
  • 8.2 OWASP LLM Top 10
  • 8.3 Responsible AI and Governance

Module 9: Offensive Security for AI Systems

  • 9.1 AI Threat Modeling
  • 9.2 AI System Attacks
  • 9.3 AI Red Teaming Concepts

Module 10: Security Operations, Incident Response and Malware Analysis

  • 10.1 SOC and Incident Response Basics
  • 10.2 Malware and Threat Analysis
  • 10.3 AI-Assisted SOC Operations

Module 11: Governance, Compliance and Ethical AI Security

  • 11.1 Governance and Risk Management
  • 11.2 Compliance and Privacy
  • 11.3 Ethical and Responsible Security

Module 12: Capstone Project — AI-Driven Security Operations and Defense

  • 12.1 Phase 1: Reconnaissance and Environmental Review
  • 12.2 Phase 2: Detection and Threat Analysis
  • 12.3 Phase 3: AI Security Assessment
  • 12.4 Phase 4: Incident Response
  • 12.5 Phase 5: Governance and Reporting

AI Agents for AI+ Security Practitioner

  • 1.1 What Are AI Agents?
  • 1.2 Key Capabilities of AI Agents in Cyber Security
  • 1.3 Applications and Trends for AI Agents in Cyber Security
  • 1.4 How Does an AI Agent Work?
  • 1.5 Core Characteristics of AI Agents
  • 1.6 Types of AI Agents

Předpokládané znalosti

Tato část není lokalizována

  • Basic understanding of AI and cybersecurity concepts, including security principles and terminology.
  • Knowledge of security operations such as threat detection, risk management, vulnerability assessment, and incident response.
  • Familiarity with networking, systems, cloud environments, and security controls.
  • Understanding data protection, privacy, compliance, and secure data handling practices.
  • Basic programming and automation awareness for security workflows.
  • Awareness of responsible AI, security governance, and AI-powered security tools.

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