PortfolioDive editorial guide · Review official vendor requirements before scheduling an exam or purchasing any training.
Start with the problem, not a list of tools
AI covers machine learning, language models, automation and many other topics. Pick a clear outcome—such as answering customer questions from documents—then work backward to the tools required.
Learn the foundations
Get comfortable with basic Python, APIs, JSON and Git. Study the difference between a trained model, an inference API, embeddings and retrieval. You do not need to train a large model from scratch to build useful applications.
Build something small
Create an assistant that answers questions from a short set of documents. Add source references, test examples, and a fallback when the documents do not contain the answer.
Show your work
Publish a GitHub repository and explain the architecture, tradeoffs, safeguards, costs and what you learned. Employers and clients can evaluate this more easily than a list of buzzwords.