Coursera
SubscriptionGovernance for Generative AI
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The course applies corporate governance principles to AI ethics, compliance and risk management in organizations. It starts with generative AI basics, including its capabilities and the challenges it creates in corporate settings, so readers without a GenAI background can follow along.
Cybersecurity topics cover data privacy, adversarial attacks and mitigation. The risk material looks at misinformation, bias, regulatory exposure and operational weak points, which are typical concerns for leadership teams.
Two case studies anchor the course: building a governance program for GenAI, and using Azure Policy to enforce governance and compliance in cloud AI systems. The Azure example makes it most relevant to teams already working on Microsoft cloud.
Listed for all levels and aimed at IT professionals.
This course contains the use of artificial intelligence.
Governance for Generative AI is a meticulously structured Udemy course aimed at IT professionals seeking to master Governance for Generative AI to leverage the power of generative AI. This course systematically walks you through the initial basics to advanced concepts with applied case studies. You will gain a deep understanding of the principles and practices necessary for effective governance. The course combines theoretical knowledge with practical insights to ensure comprehensive learning. By the end of the course, you'll be equipped with the skills to implement governance frameworks that align with your enterprise's strategic goals.
By learning Governance for Generative AI, you're gaining proficiency on how to effectively govern GenAI in your enterprise.
Key Benefits for you:
Basics - Generative AI: Gain a foundational understanding of generative AI, its capabilities, applications, and the challenges it presents in corporate environments.
Corporate Governance: Explore the principles of corporate governance and how they apply to AI ethics, compliance, and risk management in organizations.
Cybersecurity for Generative AI: Learn about the security risks associated with generative AI, including data privacy, adversarial attacks, and mitigation strategies.
Risks for Generative AI: Examine the key risks generative AI poses, such as misinformation, bias, regulatory concerns, and operational vulnerabilities.
Case Study - Building a Governance Program for GenAI: Analyze a real-world example of how organizations develop and implement governance frameworks to manage AI risks effectively.
Case Study - AI Governance with Azure Policy: Explore how Azure Policy can be leveraged to enforce AI governance, ensuring compliance and security in cloud-based AI systems.
This course contains promotional materials.
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Ethics and Governance in the Age of Generative AI
