Pulling Data Out of a Hat - The Magic of Democratised AI

Overview

Discover how cutting-edge AI can deliver "magic" for users and learn about democratizing AI to scale across organizations, as explained by LinkedIn's CDO Igor Perisic.

Syllabus

• Course Introduction
Overview of Course Objectives
Introduction to Igor Perisic and his Contributions to AI
• Understanding the Basics of AI and Democratised AI
Definition and Core Concepts of AI
What is Democratised AI?
Benefits and Challenges of Democratizing AI
• Cutting-edge AI Technologies
Overview of Current AI Technologies
How AI Technologies are Creating "Magic"
Case Studies of Successful AI Implementations
• The Role of Data in AI
Understanding Data Collection and Management
Data Privacy and Ethical Considerations
Techniques for Extracting Value from Data
• Scaling AI Across Organizations
Best Practices for Implementing AI at Scale
Overcoming Barriers to AI Adoption
Tools and Frameworks for Scaling AI
• AI Governance and Ethical Considerations
Ethical Implications of AI at Scale
Developing AI Governance Frameworks
Ensuring Fairness and Accountability in AI Deployments
• Democratizing AI: Tools and Technologies
Overview of Democratization Tools
Hands-on Session: Using AI Tools in Practice
Platforms Supporting AI Democratization
• Real-world Applications and Case Studies
Success Stories from LinkedIn
Other Notable Industry Examples
Learning from Failures: Key Takeaways
• Conclusion and Future Trends
Summarizing Key Learning Points
The Future of AI and Democratization
Resources for Continued Learning
• Course Review and Final Assessment
Recap and Q&A Session
Final Project/Assessment
Feedback and Course Evaluation

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Subjects

Conference Talks