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AI and Compliance Certification

This course is designed to provide practitioners with a comprehensive understanding of compliance issues related to artificial intelligence (AI). It covers regulatory frameworks, ethical considerations, risk management, and practical applications to ensure AI systems are developed and deployed responsibly and legally.

Online Course
Self Paced

Launch date

04 July


8 Hours



What you are going to learn

AI and Compliance Certification

Learning Outcomes
  • Understand the fundamentals of AI and the importance of compliance
  • Gain proficiency in using compliance tools and techniques for AI
  • Develop skills in risk management and incident response for AI systems
  • Apply data privacy and protection measures in AI projects
  • Explore practical applications and case studies of AI compliance

  • Basic understanding of AI concepts and technologies
  • Familiarity with compliance concepts and regulations
  • Knowledge of data analytics and risk management is a plus

This course is designed for compliance officers, legal professionals, AI developers, data scientists, and anyone interested in understanding and implementing compliance in AI systems.

Course Outline
Module 1: Introduction to AI and Compliance
- Understanding AI
- Importance of AI Compliance

Module 2: Regulatory Landscape for AI
- Global Regulatory Frameworks
- Specific Regulations and Guidelines
- Sector-Specific Regulations

Module 3: Ethical Considerations in AI
- AI Ethics Frameworks
- Bias and Fairness in AI
- Transparency and Explainability

Module 4: Risk Management in AI
- Identifying and Assessing Risks
- Developing a Risk Management Strategy
- Incident Response and Reporting

Module 5: Data Privacy and Protection
- Privacy Regulations
- Data Protection Techniques
- User Privacy and Consent

Module 6: Compliance Tools and Techniques
- AI Audit and Governance Tools
- Monitoring and Reporting
- Ethical AI Toolkits

Module 7: Practical Applications and Case Studies
- Project 1: Implementing GDPR Compliance in an AI System
- Project 2: Bias Mitigation in Machine Learning Models