Courses AI certifications (AI CERTs®)

AI+ Ethics Fundamentals™

  • Price 109 EUR + VAT
  • E-learning Start any time
  • Duration 8 hours of content, self-paced
  • Language English
  • Topic AI Business

How you can take it

  • E-learning Start any time · 109 EUR + VAT Order
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Overview

What the course covers

The course, the materials and the exam are in English. The description below is the original AI CERTs® text.

  • Responsible AI Focus: Master ethical AI use aligned with business and societal values
  • Risk Mitigation: Learn to manage compliance, transparency, and AI decision-making
  • Strategic Guidance: Integrate ethical practices into AI adoption and leadership
  • Reputation Builder: Build organisational trust and credibility in AI deployments

Prerequisites

Basic knowledge of artificial intelligence, machine learning concepts, Python familiarity, fundamental AI/ML concepts

Audience

Who is it for

Ethics Professionals: Enhance your expertise in AI ethics to guide responsible AI deployment.

AI & Data Enthusiasts: Learn how to apply ethical frameworks in AI decision-making processes.

Compliance Officers: Ensure AI technologies comply with legal and ethical standards to mitigate risks.

Technology Leaders: Drive ethical AI strategies and lead responsible AI initiatives within organizations.

Students & New Graduates: Gain a competitive edge in the rapidly growing field of AI ethics.

In the price

What the price includes

  • Self-paced online course with the full learning material
  • The official AI CERTs® exam
  • Digital badge after passing the exam

Course content

Syllabus

Course Overview
  • Course Introduction Preview
Module 1: Foundations of AI Ethics and Responsible AI
  • 1.1 Understanding AI in a Modern Ethics Context
  • 1.2 The Societal Impact of AI Technologies
  • 1.3 Core Principles and Stakeholders
  • 1.4 Building AI Literacy for the Workplace
  • 1.5 Human Rights, Democracy, and AI Ethics
  • 1.6 Case Studies
Module 2: Bias, Fairness, and Inclusion in AI
  • 2.1 Where Bias Enters AI Systems
  • 2.2 Fairness Concepts and Practical Evaluation
  • 2.3 Mitigation and Inclusive Design
  • 2.4 Applied Fairness Cases
  • 2.5 Case Studies
Module 3: Transparency, Explainability, and Documentation
  • 3.1 Why Transparency Matters
  • 3.2 Explainability Methods and Documentation Standards
  • 3.3 Communicating AI Decisions Responsibly
  • 3.4 Transparency, Documentation, and Governance Practices
  • 3.5 Case Studies
Module 4: Privacy, Security, and AI Data Governance
  • 4.1 Privacy Principles in AI
  • 4.2 AI Data Governance and Data Quality
  • 4.3 Security Risks in AI Systems
  • 4.4 Privacy-Preserving AI Techniques
  • 4.5 Content Authenticity, Provenance, and Trust
  • 4.6 Real World Case Studies
Module 5: Accountability, Oversight, and AI Governance
  • 5.1 Accountability Across the AI Lifecycle
  • 5.2 Human Oversight and Control
  • 5.3 Risk Management and Assurance
  • 5.4 Red Teaming and Safety Testing
  • 5.5 Governance Operating Model
  • 5.6 Grievance and Remedy Processes
  • 5.7 System Retirement and Decommissioning
  • 5.8 Applied Case Studies
Module 6: Legal, Regulatory, and Standards Landscape
  • 6.1 International Principles and Treaties
  • 6.2 Management and Technical Standards
  • 6.3 Binding Regional Laws
  • 6.4 National Guidance and Voluntary Frameworks
  • 6.5 Sector-Specific and Cross-Border Compliance
  • 6.6 Case Studies
Module 7: Generative AI, Agentic AI, and Responsible Deployment
  • 7.1 How Modern Generative and Agentic AI Systems Work
  • 7.2 New Risks Introduced by Generative AI
  • 7.3 Agentic AI Risks and Governance
  • 7.4 Evaluation and Safe Deployment
  • 7.5 Responsible Use Cases and Boundaries
Module 8: Capstone - AI Ethics Impact Assessment and Governance Plan
  • 8.1 Select an AI Use Case
  • 8.2 Perform an Ethics and Risk Assessment
  • 8.3 Develop an AI Governance Package Using the NIST AI RMF
  • 8.4 Final Capstone Deliverable
  • 8.5 Review and Reflection
Optional Module: AI Agents for Ethics
  • 1.1 What Are AI Agents?
  • 1.2 Applications and Trends of AI Agents for Ethics
  • 1.3 How Does an AI Agent Work?
  • 1.4 Core Characteristics of AI Agents
  • 1.5 Importance of AI Agents
  • 1.6 Types of AI Agents

Exam

About the exam

  • 50 Questions
  • 90 min Time limit
  • 70% Pass mark
  • Online proctored exam

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Any of our courses can be delivered as private, in-company training, tailored to your organisation, in English or Hungarian.

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