Data Analytics, MLops, AI assistants such as Claude and Copilot, auditability, model governance, LLM-enabled analytics, RAG patterns, MCP for connecting assistants to tools and data sources, data literacy, PII handling, prompt tool safety, summarization with responsible AI controls, product development life cycle, retraining triggers, monitoring drift, semantic search, ModelOps, explainability evaluation