Regression, Data Mining, Text Mining, Forecasting using R

Prompt engineering is the practice of composing what you send a generative model, the instruction, the supporting material and the worked examples, so that it returns something you can actually use.

Retrieval-augmented generation is a pattern that searches a body of documents when a question arrives and places the passages it finds into the model's prompt, so the answer is drawn from those sources rather than from training alone.

Natural language processing is the area of AI that makes human language readable and writable by machine: sorting text into categories, pulling structured facts out of it, translating it, generating it and measuring whether any of that came out right.

Data visualisation is the practice of encoding numbers as position, length and colour so that a comparison a reader would otherwise have to calculate becomes something they can simply see.

Data engineering is the discipline of moving records from the systems that produce them into a store where they can be queried, and of keeping that supply correct while the sources underneath keep changing.

SQL is the declarative language for asking questions of relational databases: you state which rows and columns you want and how tables relate, and the database engine works out how to retrieve them.