Learn DBT from Scratch

Computer vision is the branch of artificial intelligence that turns images and video into structured answers: what is in the frame, where it sits, which pixels belong to it, and where it moves next.

Agentic AI is software that wraps a language model in a loop where it can request actions from real tools, read what each action returns, and choose the next move until the job is finished or a rule stops it.

MLOps is the engineering practice of keeping a trained model useful in production: recording what produced it, serving it, watching for the day its answers stop matching the world, and retraining or reverting before anyone downstream is harmed by the gap.

Data governance is the set of decisions and responsibilities an organisation puts in place over its data: who owns each dataset, what each field means, who may read or change it, how long it is kept and how its quality is measured, recorded so that the answers do not depend on who is asked.

Data quality is the degree to which a dataset is fit for the purpose it is used for, assessed along named dimensions, whether the records are complete, unique, consistent, timely, valid and accurate, and measured against the requirements of the decision the data supports rather than against an absolute standard.

Data modelling is the design of how data is structured for a given use: which entities are recorded, which attributes describe them, how the tables relate through keys, and, for analytical use, which table holds the measurements and which hold the context, decided before the data is loaded so that the questions the model must answer run correctly and fast.