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 Duration 7 hours

Course Outline

Session Opening and Orientation

Core Principles of Artificial Intelligence

  • Foundational definitions and operational capabilities of AI
  • Distinguishing between Machine Learning, Neural Networks, and other computational models
  • Key sectors for practical implementation

Statutory and Regulatory Environment

  • Overview of the EU AI Act and its alignment with national legislative frameworks
  • Application of the General Data Protection Regulation (GDPR) to AI systems
  • Accountability and liability standards regarding AI deployment

Ethical Integrity and Public Impact

  • Mitigation of algorithmic bias and discriminatory outcomes
  • Ensuring transparency, auditability, and traceability of decisions
  • Institutional responsibility in the governance of AI tools

Technical Proficiency

  • Introduction to data analytics and machine learning methodologies
  • Fundamental comprehension of algorithmic logic and data handling
  • Operational use of standard AI platforms and utilities

Risk Governance and Control

  • Systematic identification and evaluation of potential hazards
  • Implementing controls to reduce operational errors and unauthorized use
  • Continuous oversight and periodic assessment of AI systems

Requirements

  • No prior requirements

Target Audience

  • Entities involved in the development, operation, or utilization of AI systems or tools
  • Providers and operators of high-risk AI systems
  • Organizations processing personal data within AI-based applications

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