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    AI for data and digital teams

    The build-side vocabulary: what you index, what you retrieve, and what you measure afterwards.

    10 terms · about 22 minutes · written with technical readers in mind

    Start with Data cleaning

    1. Data cleaning

      The process of checking data, fixing problems, and putting it into a usable form for analysis or model training.

      Data and Infrastructure · Starter

    2. Annotation and data labelling

      People or software tools add task-relevant tags, notes or boundaries to data for model training, testing, analysis or monitoring.

      Data and Infrastructure · Starter

    3. Embedding

      A list of numbers that places a token or other item in a mathematical space so a model can compare patterns, relationships and context.

      Transformers and Attention · Intermediate

    4. Vector database

      A specialised system stores numerical meaning-representations of content and quickly finds the closest matches to a query by semantic similarity.

      Search, Embeddings and RAG · Intermediate

    5. Semantic search

      A search method that finds material by similar meaning, not just shared words, and returns the most relevant passages for review or further AI use.

      Search, Embeddings and RAG · Starter

    6. Retrieval-augmented generation

      A method that first finds relevant source passages and then asks a language model to answer using that material.

      Search, Embeddings and RAG · Intermediate

    7. Evaluation

      Evaluation checks how well a system performs on a defined task, while metrics are the specific measures and evals are the tests used to produce them.

      Model Quality and Evaluation · Starter

    8. Distribution shift and data drift

      These terms describe mismatches between development and live data, including changed inputs, labels or relationships, which can reduce a system's reliability.

      Data and Infrastructure · Intermediate

    9. API

      An application programming interface defines rules that software uses to request data or actions from another system.

      AI Agents and Automation · Starter

    10. Deployment

      Deployment means putting an AI system into real use so people or software can send it live inputs and receive live outputs.

      Data and Infrastructure · Starter