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AI+ Ethics Fundamentals™
AC-120
Formerly known as AI+ Ethics™ Navigate the Intersection of AI and Ethics in Business Landscape
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
$195.00
- High-Quality Video, E-book & Audiobook
- Modules Quizzes
- AI Mentor
- Access for Tablet & Phone
- Online Proctored Exam with One Free Retake
- Hands-on Practices
Why This Certification Matters
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In-Depth Ethical Understanding: Understand ethical considerations and social impacts of AI for responsible decision-making.
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Bias Mitigation and Fairness: Learn strategies to identify and prevent biases in AI systems, ensuring fairness and transparency.
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Privacy and Security Assurance: Explore strategies to safeguard privacy and secure AI systems and data.
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Legal and Regulatory Compliance: Understand global AI regulations to ensure compliance with legal and ethical standards.
At a Glance: Course + Exam Overview
Program Name
AI+ Ethics Fundamentals™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Prerequisites
Basic knowledge of artificial intelligence, machine learning concepts, Python familiarity, fundamental AI/ML concepts
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Who Should Enroll?
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Ethics Professionals: Enhance your expertise in AI ethics to guide responsible AI deployment.
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AI & Data Enthusiasts: Learn how to apply ethical frameworks in AI decision-making processes.
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Compliance Officers: Ensure AI technologies comply with legal and ethical standards to mitigate risks.
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Technology Leaders: Drive ethical AI strategies and lead responsible AI initiatives within organizations.
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Students & New Graduates: Gain a competitive edge in the rapidly growing field of AI ethics.
What You'll Learn
- 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
- Course Introduction Preview
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
Tools You'll Master
Prerequisites
- Basic knowledge of artificial intelligence, machine learning concepts, Python familiarity, fundamental AI/ML concepts
Exam Details
Duration
90 minutes
Passing Score
70%
Format
50 questions
Delivery Method
online proctored exam
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
- 1 day (live or virtual) Self-Paced: 8 hours of content
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- 8 hours of content
- Learn anywhere, anytime, with modular quizzes to track progress
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