Zamość

Ośrodek Sportu i Rekreacji , Królowej Jadwigi 8 , Zamość, Poland, 22-400

The training room, located in the central part of Zamość, serves as an ideal venue for workshops. Its strategic location makes it easily accessible to participants from various parts of the city and neighboring towns. Additionally, this room stands out with its rich equipment, enabling the conduct of courses in an efficient and professional manner.

Lublin

Hotel Trzy Róże, Zemborzyce Dolne 96a, Lublin, Poland, 20-515

The training rooms are equipped with modern audiovisual equipment, enabling effective presentations and interactive training sessions. Additionally, there is fast and reliable internet available, facilitating easy access to online materials and communication with the training team. The facility is located just 9 kilometers from the center of Lublin. Situated on the main S19 route towards Kraśnik, it provides convenient access from Rzeszów, Warsaw, Łódź, and Białystok. Thanks to this central location, participants can quickly and comfortably reach the training venue, further easing event organization and ensuring participant comfort.

Explore Our Courses

AI Governance, Compliance, and Security for Enterprise Leaders

 14 Hours
This instructor-led, live training in lubelskie (online or onsite) is aimed at intermediate-level enterprise leaders who wish to understand how to govern and secure AI systems responsibly and in compliance with emerging global frameworks such as the EU AI Act, GDPR, ISO/IEC 42001, and the U.S. Executive Order on AI.By the end of this training, participants will be able to:
  • Understand the legal, ethical, and regulatory risks of using AI across departments.
  • Interpret and apply major AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001).
  • Establish security, auditing, and oversight policies for AI deployment in the enterprise.
  • Develop procurement and usage guidelines for third-party and in-house AI systems.
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Building Secure and Responsible LLM Applications

 14 Hours
This instructor-led, live training in lubelskie (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.By the end of this training, participants will be able to:
  • Understand the core vulnerabilities of LLM-based systems.
  • Apply secure design principles to LLM app architecture.
  • Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
  • Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.
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Securing AI Models: Threats, Attacks, and Defenses

 14 Hours
This instructor-led, live training in lubelskie (online or onsite) is aimed at intermediate-level machine learning and cybersecurity professionals who wish to understand and mitigate emerging threats against AI models, using both conceptual frameworks and hands-on defenses like robust training and differential privacy.By the end of this training, participants will be able to:
  • Identify and classify AI-specific threats such as adversarial attacks, inversion, and poisoning.
  • Use tools like the Adversarial Robustness Toolbox (ART) to simulate attacks and test models.
  • Apply practical defenses including adversarial training, noise injection, and privacy-preserving techniques.
  • Design threat-aware model evaluation strategies in production environments.
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Introduction to AI Security and Risk Management

 14 Hours
This instructor-led, live training in lubelskie (online or onsite) is aimed at beginner-level IT security, risk, and compliance professionals who wish to understand foundational AI security concepts, threat vectors, and global frameworks such as NIST AI RMF and ISO/IEC 42001.By the end of this training, participants will be able to:
  • Understand the unique security risks introduced by AI systems.
  • Identify threat vectors such as adversarial attacks, data poisoning, and model inversion.
  • Apply foundational governance models like the NIST AI Risk Management Framework.
  • Align AI use with emerging standards, compliance guidelines, and ethical principles.
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