Name: Data Security in the age of Generative AI
Availability: InStock

What You'll Learn

Discover how Generative AI systems process data from training to output, and pinpoint where security vulnerabilities can appear.
Analyze why organizations restrict access to AI tools and how enterprise-level controls protect sensitive information.
Classify different types of data—public, internal, confidential, and regulated—to decide what can safely be shared with GenAI tools.
Apply masking, anonymization, and safe prompting techniques to prevent accidental data exposure during AI-assisted work.
Identify real-world cases of prompt injection and recognize how malicious instructions can be hidden inside everyday text or documents.
Differentiate between direct and indirect prompt injection attacks and evaluate how each one compromises AI behavior.
Implement defensive habits such as separating instructions from content, setting clear prompt boundaries, and auditing outputs for accuracy and risk.
Use the STOP Method (Scan, Test, Observe, Pause) to review AI-generated outputs before sharing or publishing them.
Adopt the “Validate → Escalate → Approve” review framework to ensure AI outputs meet organizational accuracy, privacy, and compliance standards.
Develop a proactive mindset for identifying, reporting, and mitigating GenAI-related security incidents within your workplace.

Requirements

No prior experience with data security or AI is required — all key concepts are explained from the ground up.

Managers and team leads who want to establish responsible AI usage practices within their departments.
Leaders and decision-makers who want to build organization-wide trust and accountability in the adoption of Generative AI.
Corporate professionals who want to use Generative AI tools safely without violating company data policies.
Data analysts and engineers who want to prevent data leaks while integrating AI into their workflows.
HR and compliance officers who want to ensure employee and client information remains protected in AI-assisted tasks.
Consultants and freelancers who want to handle client data responsibly when using Generative AI platforms.
Leaders and decision-makers who want to build organization-wide trust and accountability in the adoption of Generative AI.

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