Certified AI Governance Professional (AIGP)
Master the intricacies of artificial intelligence governance with our specialized training program designed by industry experts. This comprehensive course covers everything from fundamental concepts to advanced regulatory frameworks ensuring you acquire a robust skill set in responsible AI management. Enroll now to become a certified professional adept at navigating the complexities of AI systems.
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What you'll learn
- Differentiate between narrow AI and general AI systems.
- Implement continuous monitoring and auditing frameworks for deployed AI systems.
- Explore ethical challenges associated with AI such as bias and discrimination.
- Develop skills in risk management throughout the AI development lifecycle.
- Learn about various machine learning models including supervised, unsupervised, and reinforcement learning.
- Gain insights into global regulatory frameworks governing AI systems.
- Understand fundamental concepts of artificial intelligence (AI) and machine learning.
Why should you attend?
This course provides a comprehensive exploration of the multifaceted world of artificial intelligence (AI) governance. It begins with an introduction to the fundamental concepts and definitions of AI and machine learning, offering a socio-technical context for understanding these technologies. Participants will gain insights into various types of AI systems, including narrow AI, general AI, and different machine learning models such as supervised, unsupervised, and reinforcement learning. The course also covers advanced topics like deep learning, generative AI, and natural language processing. The curriculum delves into the AI technology stack, discussing platforms, applications, and the necessary hardware and software infrastructure. Responsible AI principles are emphasized, highlighting risks at individual, societal, and organizational levels while focusing on transparency, fairness, and accountability. Ethical challenges such as bias and discrimination are addressed alongside strategies for managing AI's societal impact. Participants will explore global AI laws and regulatory frameworks like the EU AI Act and GDPR intersections. The course outlines key steps in the AI development lifecycle and governance roles across stakeholders. Emerging regulations and standards are examined in-depth, comparing major risk management frameworks from ISO to IEEE. Risk management techniques for AI design, development, and deployment are discussed along with tools for responsible governance. The course includes modules on testing and validating AI systems for trustworthiness and performance. Post-deployment monitoring ensures continuous risk assessment and compliance through auditing frameworks. Finally, participants can test their knowledge with full-length practice exams that include detailed reviews of answers.
Course Syllabus
Day 1 - AI Fundamentals and Systems
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Responsible AI Governance
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Ratings and Reviews
Instructor
FAQ
Frequently Asked Questions About This Course
Courses you may like
Why should you attend?
This course provides a comprehensive exploration of the multifaceted world of artificial intelligence (AI) governance. It begins with an introduction to the fundamental concepts and definitions of AI and machine learning, offering a socio-technical context for understanding these technologies. Participants will gain insights into various types of AI systems, including narrow AI, general AI, and different machine learning models such as supervised, unsupervised, and reinforcement learning. The course also covers advanced topics like deep learning, generative AI, and natural language processing. The curriculum delves into the AI technology stack, discussing platforms, applications, and the necessary hardware and software infrastructure. Responsible AI principles are emphasized, highlighting risks at individual, societal, and organizational levels while focusing on transparency, fairness, and accountability. Ethical challenges such as bias and discrimination are addressed alongside strategies for managing AI's societal impact. Participants will explore global AI laws and regulatory frameworks like the EU AI Act and GDPR intersections. The course outlines key steps in the AI development lifecycle and governance roles across stakeholders. Emerging regulations and standards are examined in-depth, comparing major risk management frameworks from ISO to IEEE. Risk management techniques for AI design, development, and deployment are discussed along with tools for responsible governance. The course includes modules on testing and validating AI systems for trustworthiness and performance. Post-deployment monitoring ensures continuous risk assessment and compliance through auditing frameworks. Finally, participants can test their knowledge with full-length practice exams that include detailed reviews of answers.
What you'll learn
- Differentiate between narrow AI and general AI systems.
- Implement continuous monitoring and auditing frameworks for deployed AI systems.
- Explore ethical challenges associated with AI such as bias and discrimination.
- Develop skills in risk management throughout the AI development lifecycle.
- Learn about various machine learning models including supervised, unsupervised, and reinforcement learning.
- Gain insights into global regulatory frameworks governing AI systems.
- Understand fundamental concepts of artificial intelligence (AI) and machine learning.
Course Syllabus
Day 1 - AI Fundamentals and Systems
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - Responsible AI Governance
Short Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Public Pricing
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Subsidies
Ratings and Reviews
Instructor
Courses you may like
FAQ
Frequently Asked Questions About This Course
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