Opinion: AI Students Should Build Projects, Not Just Collect Certificates

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A DEV Community article argues that many AI and machine learning learners in 2026 are accumulating certifications without building practical projects, leaving them unable to answer basic interview questions about their work. The piece recommends a progression of hands-on projects, starting with data analysis and predictive modeling using public datasets. It then advises building deployable machine learning applications, semantic search systems using embeddings and vector databases, and finally Retrieval-Augmented Generation (RAG) assistants. The author emphasizes that the learning value lies in the process — handling edge cases, debugging retrieval errors, and explaining design decisions — rather than achieving high accuracy scores. The article positions project-based learning as the most effective way to develop genuine, interview-ready AI skills.

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