AI+ Security Level 1™ 

• Aspiring Cybersecurity Professionals
• Build a strong foundation in AI-powered security practices.
• IT Administrators & Network Engineers
• Enhance your threat detection and system security capabilities.
• Developers & Programmers
• Learn how to integrate security into the software development lifecycle.
• Junior Security Analysts
• Upskill with hands-on tools and modern detection techniques.
• Ethical Hackers & Bug Bounty Hunters
• Use AI to improve penetration testing and anomaly identification.
• Students & Tech Graduates
• Enter the cybersecurity field with practical, job-ready skills.
• Career Switchers in IT
• Transition into cybersecurity with AI as your competitive edge.

• Fundamentals of AI in cybersecurity
• Using Python for building security automation
• Machine learning applications for phishing and malware detection
• AI-based anomaly and threat detection
• GANs for security simulations
• Network security and user authentication
• Real-world cybersecurity problem solving through Capstone Projects

• Basic Python Programming: Familiarity with loops, functions, and variables.

• Basic Cybersecurity Knowledge: Understanding of CIA triad and common threats (e.g., malware, phishing).

• Basic Machine Learning Concepts: Awareness of fundamental machine learning concepts, not mandatory.

• Basic Networking: Understanding of IP addressing and TCP/IP protocols.

• Linux/Command Line Skills: Ability to navigate and use the CLI effectively.

• There are no mandatory prerequisites for certification. Certification is based solely on performance in the examination. However, candidates may choose to prepare through self-study or optional training offered by AI CERTS Authorized Training Partners (ATPs).

Module 1: Introduction to Cybersecurity

• Core Concepts: Understand the foundational principles of cybersecurity, including the CIA triad (Confidentiality, Integrity, and Availability).
• Threat Landscape: Learn about common cyber threats such as malware, phishing, and social engineering.
• Defense Strategies: Explore basic security measures like firewalls, encryption, and multi-factor authentication (MFA).

Module 2: Operating System Fundamentals

• Operating System Security: Understand how to secure different operating systems (e.g., Windows, Linux) by managing user accounts, file permissions, and system configurations.
• Security Best Practices: Learn about patching, updating, and hardening operating systems to reduce vulnerabilities.
• Log Analysis: A foundational look at system logs and how they can be used to monitor for suspicious activity.

Module 3: Networking Fundamentals

• Networking Concepts: A refresher on basic networking concepts, including the OSI model, IP addressing, and common network protocols.
• Network Security: Learn about network security components like routers, switches, and intrusion detection systems (IDS).
• Network Attacks: Understand common network-based attacks and how to defend against them.

Module 4: Threats, Vulnerabilities, and Exploits

• Vulnerability Assessment: Differentiate between threats, vulnerabilities, and exploits.
• Common Vulnerabilities: Learn about common types of vulnerabilities, such as unpatched software and misconfigurations.
• Malware Analysis: An introduction to different types of malware (e.g., viruses, ransomware) and the basic techniques for analyzing them.

Module 5: Understanding of AI and ML

• Introduction to AI: An accessible introduction to the core concepts of AI and Machine Learning (ML), including supervised and unsupervised learning.
• AI in Security: Explore the benefits of using AI to analyze large datasets, automate tasks, and identify patterns that may be missed by human analysts.

Module 6: Python Programming Fundamentals

• Python for Security: Understand why Python is a primary language for cybersecurity professionals.
• Scripting for Automation: Learn to write basic Python scripts to automate repetitive security tasks, such as scanning logs or performing network scans.
• Security Tools: A practical session on using Python to build custom security tools.

Module 7: Applications of AI in Cybersecurity

• AI for Threat Detection: Learn how AI is used for real-time threat detection by analyzing network traffic and user behavior for anomalies.
• Phishing and Malware Detection: Explore how AI algorithms are trained to detect email-based threats, such as phishing and sophisticated malware.
• Predictive Analytics: Understand how AI can be used to predict future attack vectors and proactively enhance security measures.

Module 8: Incident Response and Disaster Recovery

• Incident Response Lifecycle: An overview of the incident response process, from preparation and detection to containment and recovery.
• AI in Incident Response: Learn how AI can automate incident triage, prioritize alerts, and assist in forensic analysis, significantly reducing response times.
• Disaster Recovery: A look at how AI and machine learning can be used in disaster recovery planning to simulate different scenarios and optimize recovery strategies.

Module 9: Open Source Security Tools

• Tooling Landscape: An introduction to popular open-source security tools for different cybersecurity domains.
• Incident Response Tools: Get hands-on with open-source tools for incident response and digital forensics, such as TheHive and Velociraptor.
• Vulnerability Scanning: Learn to use tools like OpenVAS to perform vulnerability scans and identify weaknesses in a network.

Module 10: Securing the Future

• Continuous Learning: A guide to staying current with the rapid pace of innovation in cybersecurity and AI.
• Career Paths: A discussion on the various career paths available in the field of AI and cybersecurity.

Module 11: Capstone Project

• Real-World Application: A hands-on project where you will apply the skills and knowledge gained throughout the course to a real-world cybersecurity problem, such as building an AI-powered phishing detector.

Optional Module: AI Agents for Security Level 1

• 1. What Are AI Agents: A foundational introduction to AI agents as autonomous systems that can perform complex, multi-step tasks to achieve a security objective.
• 2. Key Capabilities of AI Agents: Explore the basic capabilities of AI agents, such as automating simple security checks, monitoring system health, and generating basic reports.
• 3. Applications and Trends: A look at the real-world applications of entry-level AI agents in cybersecurity and a discussion of their future role in security operations.

. Explore more Security training here

Some courses may support vendor certification exams or digital badges. Exam availability depends on the specific programme and vendor requirements.