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Starts 7 June 2025 16:57

Ends 7 June 2025

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Implementing AI Responsibly and Securely - Session BRK358

Discover practical strategies and real-world examples for implementing AI solutions with a focus on ethics, security, and scalability in enterprise environments. Learn from industry experts about overcoming challenges and ensuring responsible AI deployme…
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Microsoft

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Overview

Discover practical strategies and real-world examples for implementing AI solutions with a focus on ethics, security, and scalability in enterprise environments. Learn from industry experts about overcoming challenges and ensuring responsible AI deployme…

Syllabus

  • Introduction to Responsible AI
  • Overview of AI Ethics
    Importance of Responsible AI Deployment
    Real-World Examples of Ethical AI
  • Understanding AI Security
  • Key Security Challenges in AI Systems
    Techniques for Securing AI Models and Data
    Case Studies on AI Security Breaches
  • Strategies for Scalable AI
  • Designing Scalable AI Architectures
    Implementing AI at Scale in Enterprises
    Tools and Technologies for Scaling AI
  • Ensuring Ethical AI Deployments
  • Bias Mitigation Techniques
    Fairness and Transparency in AI Models
    Regulatory Compliance and AI Governance
  • Overcoming Challenges in AI Implementation
  • Common Pitfalls in AI Projects
    Risk Management Strategies
    Lessons Learned from AI Deployment Failures
  • Responsible AI in Practice
  • Frameworks and Guidelines for Ethical AI
    Industry Best Practices
    Tools and Platforms for Responsible AI
  • Case Studies and Industry Insights
  • Real-World Applications of AI in Enterprises
    Insights from AI Leaders and Experts
    Analysis of Successful AI Implementations
  • Conclusion and Future Trends
  • The Evolving Landscape of AI Ethics and Security
    Future Challenges and Opportunities in AI
    Building a Culture of Responsible AI Development
  • Workshop and Interactive Session
  • Hands-On Exercises: Implementing Ethical AI
    Group Discussions on AI Responsibility and Security
    Q&A with Industry Experts

Subjects

Data Science