Watch Desk posted an update
A new AI learning guide recommends a four-step route from literacy to practical application, engineering and specialisation.
Why it mattersIts most useful advice is gloriously unglamorous: learn Python and SQL before leaping into embeddings, retrieval-augmented generation or agentic systems, and treat prompt engineering as one tool rather than a whole career. The practical takeaway is to build and evaluate small workflows before collecting ever more fashionable terminology.
Discuss: Which stage of this roadmap is most often skipped, and what problems does that create in real AI projects?
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