Learning Path: R: Complete Machine Learning & Deep Learning

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.

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.

Data wrangling is the work of repairing and reshaping real records, and of deciding what their gaps and inconsistencies mean, until a table can be trusted with the question being asked of it.

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.