Unstructured Data Engineering for AI
About this course
This course prepares learners to engineer governed unstructured data pipelines for AI training, semantic search, and RAG systems. Learners design ingestion workflows for documents and multimodal content, apply extraction and OCR-aware processing, normalize text while preserving useful structure, detect sensitive information, create chunking strategies, and enrich corpora with metadata for citation, filtering, lineage, and governance. By the end of the course, learners can build or specify unstructured ingestion workflows, evaluate extraction quality, prepare corpora for embedding or training, and apply safety and quality gates for PII, bias, source trust, and licensing risk. The course emphasizes corpus quality and governance so learners can produce reliable data assets for downstream AI systems.
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What you'll learn
- engineer unstructured data ingestion workflows
- evaluate extraction quality and corpus readiness
- detect and manage sensitive information
- apply governance standards in data handling
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