A student reached out recently with a question I hear constantly: what should she study to make sure she's employable when she graduates? She'd heard cybersecurity was booming. A friend said cloud computing was the safer bet. Someone else swore by data science.

I gave her the same advice I'd give anyone asking this question, whether they're in school or already working: stop researching which field sounds hot, and start researching what employers are actually asking for.

Those are not the same exercise, and confusing them is how a lot of tuition and study time gets spent on the wrong thing.

The Trap: Studying the Buzzword Instead of the Job

Every year, a handful of terms dominate the conversation — AI, cybersecurity, cloud, DevOps, data science. Each one is real, and each one does reflect genuine hiring demand. But "this field is growing" and "this is what will get you hired" are different claims, and students routinely act on the first while assuming it proves the second.

A growing field with thousands of open positions can still be extremely difficult to break into as an entry-level candidate, if most of those postings expect three to five years of experience. A less hyped field can be considerably easier to enter if it has a steady supply of genuinely junior-friendly roles. You cannot tell the difference by reading trend articles. You can only tell the difference by reading actual job postings.

Start With 30 Real Job Postings, Not a Major

Before choosing a course of study, or before finalizing one you've already started, find 20 to 30 actual entry-level postings in fields you're considering. Not the aspirational job you want in ten years — the realistic first job, the one with "entry-level," "associate," or "junior" somewhere in the title, or with one year of experience or less requested.

Then stop reading the job titles and start reading the requirements sections. What shows up again and again? What tools, languages, or platforms appear in posting after posting, regardless of the exact title? Patterns across dozens of real postings tell you far more about what to study than any single article ranking "the top skills of 2026."

Use AI to Do This at Scale

This is where artificial intelligence is genuinely useful — not to write your papers, but to analyze the job market itself, something that used to take a career counselor days of manual research and now takes minutes.

Collect 20 to 30 entry-level postings in the fields you're weighing. Paste them into an AI system and ask something like:

"Analyze these entry-level job postings. What skills, tools, or languages appear most frequently? Which of these are typically taught in a computer science or IT degree program, and which are usually only learned through independent projects or specific training?"

Then push further:

"Based on these postings, which of these fields has the highest ratio of genuinely entry-level openings to total openings? Which field appears to have the most postings requiring experience I couldn't reasonably have as a student?"

This turns a vague, anxiety-driven question — what should I study — into an evidence-based comparison across the actual options in front of you.

But Verify What It Tells You

AI can miscount, can be swayed by which postings happened to be popular enough to write about online, and can recommend a currently fashionable technology simply because there's a great deal written about it. Treat its output as a hypothesis, not a verdict.

If it tells you cloud computing has more entry-level openings than cybersecurity, go find that out independently — search current postings yourself, filtered specifically to entry-level, and see if the ratio holds up. If it recommends a specific certification, check whether the job postings you collected actually mention that certification, or whether it's popular in training marketing but rare in real requirements. Use AI to generate the analysis. Use the actual job market to confirm it.

You Don't Have Experience Yet — So Build Some

Here's where students face a different challenge than someone already working: you can't point to years of relevant experience, because you don't have any yet. That means the single highest-leverage thing you can do isn't collecting more certificates. It's creating evidence that you can actually do the work, before anyone is paying you to do it.

This looks different depending on the field, but the principle is constant:

• Considering software development? Build a real, working application — not a tutorial clone, something with an actual problem it solves — put it in source control, and be ready to explain the decisions you made and the bugs you had to fix.
• Considering cloud or DevOps? Deploy something to a real cloud platform, containerize it, build a small CI/CD pipeline, and document what broke and how you fixed it.
• Considering cybersecurity? Set up a home lab, work through realistic vulnerable-system exercises, and be able to describe a specific attack you identified and how you'd defend against it.
• Considering data science or analytics? Find a public dataset that actually interests you, ask a real question of it, and be prepared to explain your methodology, not just show a chart.

None of this needs to be commercial-grade. It needs to exist, and you need to be able to talk about it in specific, technical detail. An interviewer choosing between "I took a course on this" and "I built this, here's what went wrong, and here's how I solved it" will remember the second candidate.

Coursework Still Matters — It Just Isn't the Whole Answer

None of this is an argument against your degree program. Foundational coursework — data structures, operating systems, networking, databases, statistics — builds the underlying understanding that makes everything else easier to learn quickly on the job. Skipping straight to trendy tools without that foundation tends to produce candidates who can follow a tutorial but struggle the moment a real production system behaves unexpectedly.

The point isn't "coursework doesn't matter." It's that coursework alone, without evidence you can apply it, is rarely enough on its own in a competitive market. Treat your degree as the foundation, and treat independent projects and job-market research as the layer that turns that foundation into something employable.

Ask a Better Question Than "What's Hot Right Now"

The student who reached out originally wanted to know which field was safest to bet on. I think there's a better question underneath that one:

Given what I can realistically build and demonstrate before I graduate, which field has the shortest credible path from "student" to "hired"?

That answer is different for different students, depending on what genuinely interests them enough to build real projects in it, and depending on what the actual entry-level job market looks like this year, not three years ago when a headline first called a field "hot."

Use AI to analyze the market. Verify what it tells you against real postings. Then spend your time building something real, in whichever field survives that scrutiny — because a diploma plus a buzzword is common. A diploma plus something you can actually show and explain is not.