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100% fundable

AI+ Security Practitioner™

Intelligent systems are changing how we perceive and defend against digital risks. Level 1 builds the foundation – from AI-powered threat detection to robust protection architectures.

Key topics

  • Methods of AI-based risk detection and automation.
  • Current cyber threat landscapes and effective countermeasures.
  • Structural principles of secure system and network architectures.
  • Practical use of intelligent detection and analysis systems.
  • AI tools and methods for a future-ready security strategy.

Prerequisite
Those with a basic understanding of digital processes and an interest in security-related technologies can get started right away.

Target group
This course is for everyone working in technical or organizational roles who wants to understand how AI is reshaping security strategies – and how they can benefit from it.

Level 1 offers not just knowledge but direction: for confident decisions in a world where AI security is becoming a competitive advantage.

Course content
  • Scope and meaning of cybersecurity
  • Core principles and key concepts in cybersecurity
  • The CIA triad: confidentiality, integrity, and availability
  • Established frameworks and standards such as NIST and ISO/IEC 27001
  • Legal and regulatory requirements, including GDPR and HIPAA
  • Why cybersecurity matters in today's organizations
  • Pathways and career options in the security field
  • Key capabilities of operating systems: memory and process management
  • Managing user accounts and access rights
  • Access control models: ACLs, DAC, and MAC
  • Built-in security features and OS hardening settings
  • Strengthening OS security through patching and service reduction
  • Security considerations in virtualized and containerized environments
  • Trusted boot processes and safe remote access methods
  • Identifying and resolving common OS security vulnerabilities
  • Common network topologies and the TCP/IP and OSI protocol models
  • The roles of routers, switches, and firewalls in a network
  • Deploying security devices such as firewalls and IDS/IPS systems
  • Structuring networks through segmentation and security zones
  • Wireless security standards and the risks of open WEP
  • How VPNs work and when to use them
  • The purpose and function of network address translation (NAT)
  • Diagnosing and resolving common network issues
  • Threat actor profiles: from script kiddies to nation-state actors
  • AI-driven approaches to threat detection
  • Leveraging SIEM and IDS/IPS tools with AI support
  • Gathering intelligence using OSINT methods
  • Understanding how vulnerabilities arise and are categorized
  • Embedding AI-assisted security into the software development lifecycle
  • Managing zero-day vulnerabilities and patch processes
  • AI-powered tools for scanning and identifying vulnerabilities
  • Practical exercises in identifying and exploiting weaknesses
  • Core concepts and origins of artificial intelligence
  • Different AI types and their areas of application
  • Recognizing and reducing risks in daily digital environments
  • Creating flexible, AI-enhanced security architectures
  • How CSAI strengthens digital protection
  • Putting machine learning to work in security scenarios
  • Safeguarding critical assets against diverse cyber threats
  • Approaches to proactive threat analysis and active threat hunting
  • Getting started with Python as a programming language
  • Exploring key Python libraries for security work
  • Applying Python in real-world cybersecurity scenarios
  • Writing AI-assisted scripts to automate security workflows
  • Analyzing and processing security data using Python
  • Building practical security tools from scratch in Python
  • How machine learning transforms security operations
  • Detecting unusual behavior through AI-driven anomaly analysis
  • Shifting from reactive to proactive defense with machine learning
  • Identifying malicious emails with machine learning models
  • AI approaches to catching phishing attempts before they succeed
  • Self-directed systems that detect and counter email attacks
  • Applying advanced algorithms and AI to identify and block malware
  • Practical steps for malware analysis and mitigation
  • Strengthening authentication through intelligent AI methods
  • Conducting AI-supported penetration tests
  • Phases of incident response: from identification through recovery
  • The full lifecycle of managing a security incident
  • Developing a structured and actionable incident response plan
  • Methods for detecting and analyzing security events
  • Steps to contain, eradicate, and restore after an incident
  • Review and improvement actions following a security event
  • Forensic techniques for collecting and preserving digital evidence
  • Planning for business continuity and data recovery
  • Using penetration tests to uncover and address weaknesses
  • Understanding legal obligations when handling security incidents
  • An overview of the open-source security tooling landscape
  • Widely used tools and what they are designed for
  • Benefits and limitations of open-source security solutions
  • Integrating open-source tools into enterprise environments
  • Tapping into community knowledge and available support resources
  • Running scans to identify network weaknesses and vulnerabilities
  • Open-source SIEM platforms for centralized event monitoring
  • Configuring and using open-source packet filtering firewalls
  • Ethical use of password analysis and hashing tools
  • Conducting digital investigations with open-source forensic software
  • The evolving threat landscape and emerging attack patterns
  • How AI and ML are reshaping the security field
  • Using blockchain technology to enhance data integrity and trust
  • Securing connected devices and IoT ecosystems
  • Protecting workloads and data in cloud environments
  • What quantum computing means for encryption and security
  • Defending critical infrastructures such as energy grids and healthcare systems
  • Fundamentals of modern cryptographic methods and secure hashing
  • Building a security-conscious culture through targeted training
  • Ongoing monitoring strategies for sustained protection
  • Project overview and learning objectives
  • Real-world scenarios applying AI to security challenges
  • Presenting and reflecting on findings and outcomes
  • Foundations and design of AI agent systems
  • Defining AI agents and their core concepts
  • How AI agents contribute to security operations
  • Current use cases and future directions for AI agents in security
  • The reasoning and decision-making process behind AI agents
  • Distinguishing characteristics of modern AI agents
  • An overview of different AI agent architectures and variants

Up to 100% funding for your continuing education

Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.

Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.