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Learn to build a monitoring system for AI models that tracks predictions, detects anomalies, and logs performance metrics - essential skills for responsible AI development in today's regulatory landscape.
Learn to build an AI model monitoring system that tracks performance degradation and generates alerts - a critical capability highlighted by experts concerned about AI system reliability.
Learn to build a keystroke data collection system similar to Meta's employee tracking program, including database design, data collection, and basic analysis capabilities.
Learn how to build a basic AI compliance checker using Python that evaluates AI decisions against predefined rules for fairness, transparency, and ethical use.
Learn to build a basic agentic AI monitoring system that demonstrates the core concepts behind Cisco's DefenseClaw, which aims to make enterprise AI safer through orchestration.
Learn to create a basic AI infrastructure monitoring dashboard that demonstrates why human oversight is crucial for managing complex AI systems.
Learn to build an AI model monitoring system that tracks performance, detects drift, and ensures compliance with government regulations - similar to the challenges faced by companies like Anthropic in their legal battles with the Department of Defense.