AI+ Security Practitioner™
Formerly known as AI+ Security Level 1™ <br> <br> Empowering Cybersecurity with AI
Certificate Code:
AT-2101
About This Course
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.
Certificate Overview
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
Prerequisites
Basic AI, cybersecurity, networking, security operations, data protection, programming, and responsible AI knowledge.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Course Modules
1
Module 1: Computing, Linux, and Operating System Foundations
- 1.1 Computing Fundamentals
- 1.2 Linux Essentials
- 1.3 Access Control Concepts
2
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
3
Module 3: Python for Security and Automation
- 3.1 Python Fundamentals
- 3.2 Python for Security
- 3.3 Security Data Analysis
4
Module 4: Cybersecurity Foundations and Threat Landscape
- 4.1 Core Cybersecurity Concepts
- 4.2 Common Cyber Threats
- 4.3 Security Frameworks
5
Module 5: Cryptography, Authentication & Identity Security
- 5.1 Cryptography Basics
- 5.2 Authentication and Identity
- 5.3 Identity Security Risks
6
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
7
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
8
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
9
Module 9: Offensive Security for AI Systems
- 9.1 AI Threat Modeling
- 9.2 AI System Attacks
- 9.3 AI Red Teaming Concepts
10
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
11
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
12
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
13
Optional Module: 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
AI Tools You'll Learn
Scikit-learn
TensorFlow
PyTorch
Kali Linux
Wireshark
Nmap
Wazuh
Splunk
