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Blogs

Featured Blogs

From Non-Technical to AI Engineer: What the Career Path Actually Looks Like in 2026

You might have been Googling "how to become an AI engineer" for a while now. The results are not helping. Some articles tell you to get a computer science degree. Others say you can be job-ready in eight weeks. A few insist you need a PhD to do anything meaningful with machine learning.A lot of what’s out there is confusing or mismatched to your background. This article is for people who are currently in non-technical roles, and are asking a more specific question: Is AI engineering a realistic career move for someone without a technical background, and if so, what does the actual path look like?

AI Engineering in 2026 — Certificate Program vs. Degree vs. Work-Integrated Training: An Honest Comparison

You are a working engineer or a career builder at a crossroads. Maybe you already know how to build software and want to specialize in AI. You might also be coming from a non-technical background and recognize that AI skills are becoming the differentiator between the role you have and the one you want. Either way, you have the same problem: the options in front of you feel either too slow, too shallow, or too expensive.Every article you have read either sells you on one path or tells you the comparison is simple. It is not.This blog will walk you through what each path actually delivers, where it has limitations, and how to match the right option to your current situation.

Introducing: UofU ProEd’s New Work-Integrated Programs!

UofU ProEd // Flatiron new Work-Integrated Immersive programs are designed for students who want a high-bar path into building products. Our Immersive students learn through structured coursework and support while also working with an employer as a paid apprentice.