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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
Testimonials (2)
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt