AI+ Security Level 1™

Price
Net: 1.985,00 €
VAT.: 377,15 €

Duration
5 days

For companies and job seekers:
this course is 100% fundable!

Location

Course Language
English

Training Solutions
WalkIn^®

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New security standards are shaping everyday digital life, with AI setting the pace. This training course provides a modern understanding of smart protection mechanisms and shows how innovative technologies can identify risks at an earlier stage.

Key topics

AI-based risk analysis and automation.
Modern cyber threat trends and defense strategies.
Fundamentals of secure system architectures.
Use of intelligent detection models.
Future-oriented security methods with AI tools.

Prerequisites
Basic knowledge of digital systems and an interest in security-related technologies.

Target audience
Individuals from technical and organizational areas who want to understand and apply AI-supported security.

This creates a solid foundation for confident decision-making in a networked future characterized by dynamic risks and intelligent protection concepts.

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Course content

Introduction to Cybersecurity

Definition and scope of cybersecurity
Key concepts of cybersecurity
CIA triad (confidentiality, integrity, availability)
Cybersecurity frameworks and standards (NIST, ISO/IEC 27001)
Cybersecurity laws and regulations (e.g., GDPR, HIPAA)
Importance of cybersecurity in modern businesses
Career opportunities in cybersecurity

Fundamentals of the operating system

Core functions of the operating system (memory management, process management)
User accounts and permissions
Access control mechanisms (ACLs, DAC, MAC)
Security functions and configurations of the operating system
Improving operating system security (patching, deactivating unnecessary services)
Security aspects of virtualization and containerization
Secure startup and secure remote access
Security vulnerabilities in the operating system and how to fix them

Fundamentals of networking

Network topologies and protocols (TCP/IP, OSI model)
Network devices and their functions (routers, switches, firewalls)
Network security devices (firewalls, IDS/IPS)
Network segmentation and zoning
Security in wireless networks (WPA2, vulnerabilities of Open WEP)
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)
Methods for threat detection using AI
AI tools for threat detection (SIEM, IDS/IPS)
Open-source intelligence techniques (OSINT)
Introduction to vulnerabilities
Software development life cycle (SDLC) and security integration with AI
Zero-day attacks and patch management strategies
Tools and techniques for scanning vulnerabilities with AI
Exploiting vulnerabilities (hands-on exercises)

Fundamentals of AI and ML

An introduction to AI
Types and areas of application of AI
Identifying and mitigating risks in everyday life
Building a resilient and adaptable security infrastructure with AI
Improving digital defenses with CSAI
Application of machine learning in cybersecurity
Protecting sensitive data and systems from a wide range of cyber threats
Concepts of threat analysis and threat hunting

Fundamentals of Python Programming

Introduction to Python Programming
Understanding Python libraries
The Python programming language for cybersecurity applications
AI scripting for automating cybersecurity tasks
Data analysis and processing with Python
Developing security tools with Python

Applications of AI in cybersecurity

Understanding the application of machine learning in cybersecurity
Anomaly detection for behavioral analysis
Dynamic and proactive defense using machine learning
Using machine learning to detect email threats
Improving phishing detection with AI
Autonomous identification and defense against email threats
Use of advanced algorithms and AI to detect malware threats
Identifying, analyzing, and defending against malware
Improving user authentication with AI techniques
Penetration testing with AI

Incident response and disaster recovery

Incident response process (identification, containment, elimination, recovery)
Incident response lifecycle
Creating an incident response plan
Incident detection and analysis
Containment, elimination, and recovery
Post-incident measures
Digital forensics and evidence preservation
Disaster recovery planning (backups, business continuity)
Penetration testing and vulnerability analysis
Legal and regulatory aspects of security incidents

Open-source security tools

Introduction to open source security tools
Popular open source security tools
Advantages and challenges of using open source tools
Implementing open source solutions in enterprises
Community Support and Resources
Network security scans and vulnerability detection
Security information and event management (SIEM) tools (open-source options)
Open-source packet filter firewalls
Password hashing and cracking tools (ethical use)
Open-source forensic tools

Securing the future

New cyber threats and trends
Artificial intelligence and machine learning in cybersecurity
Blockchain for security
Security in the Internet of Things (IoT)
Cloud security
Quantum computing and its impact on security
Cybersecurity in critical infrastructures
Cryptography and secure hashing
Cybersecurity awareness and training for users
Continuous security monitoring and improvement

Capstone project

Introduction
Use cases: AI in cybersecurity
Presentation of results

Optional module: AI agents for security level 1

Understanding AI agents
What are AI agents?
Key functions of AI agents in cybersecurity
Applications and trends for AI agents in cybersecurity
How does an AI agent work?
Key features of AI agents
Types of AI agents

Your training will be 100% funded

Our funding schemes are available exclusively to participants who live or work in Germany. Funding is not available outside Germany.

For career starters, job seekers, career changers, startups, experienced professionals, those looking to advance their careers, specialists, etc.

The QCG program for everyone in the company

Further information

The education voucher for all job seekers

Further information

Frequently asked questions

What does AI security mean?

AI security describes protective measures to safeguard AI systems against attacks, data loss, and misuse. It involves the secure development, use, and control of artificial intelligence.

Why is AI security so important?

AI systems process sensitive data. Without protection, they can be manipulated, hacked, or used incorrectly. Security ensures trust, stability, and protection against cyberattacks.

What threats exist for AI systems?

Common risks include data manipulation, model poisoning, uncontrolled automation, and deepfakes. Incorrect decisions due to faulty training data are also among these risks.

How does AI Security Level 1™ training work?

The basics are taught: safe AI use, risk assessment, types of attacks, ethical aspects, and initial protective mechanisms. The focus is on understanding, recognition, and response.

What are best practices for safe AI use?

Secure data sources, transparency, ethical evaluation, regular review, access controls, and interdisciplinary collaboration are among the key recommendations.

What tools are used in AI+ Security Level 1™?

Practical cybersecurity tools such as Microsoft Defender, Google Chronicle, IBM QRadar, Nessus, OpenVAS, and Security Onion are used. These are supplemented by cloud security solutions and threat analysis platforms directly via the browser.

What happens after AI+ Security Level 1™?

The program is structured in further stages. More in-depth technical knowledge, practical exercises, industry-specific applications, and certified advanced training courses offer long-term development opportunities.

Do you have any further questions? Please contact us.

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