Description
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This course covers the essential practices and tools for managing large language models (LLMs) in production environments. It focuses on how to responsibly and efficiently handle LLMs throughout their lifecycle, from data acquisition to insights interpretation. Learners will explore Responsible AI principles, fairness, safety, privacy, and data protection, alongside operational techniques for deploying and monitoring LLM applications.
What you'll learn
- Understand the importance of fairness, bias elimination, reliability, and safety in LLMs.
- Learn techniques to ensure privacy and protect data during model development and deployment.
- Focus on data management practices for optimizing LLM performance.
- Learn to define rules that govern prompts and responses to ensure responsible model outputs.
- Assess LLM performance with known prompts to identify potential issues.
- Implement techniques to collect telemetry data, monitor model behavior, and detect issues in production.
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