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NoDegreeTech

How to Break Into Tech (Even If You’re Starting from Zero)

You probably thought you needed a degree—or years of coding—to break into tech. You are not alone. But it turns out, there’s another way. And it’s a lot more accessible than you think.

Cyrille M. Njume

• 3 min read
How to Break Into Tech (Even If You’re Starting from Zero)
Photo by Ales Nesetril / Unsplash

Your No-Fluff, Beginner-Friendly Roadmap Into AI, Data Science, and No-Code Careers

You want to get into tech. You have no degree. You’re not some coding prodigy. And you probably think people in AI wake up speaking Python and drinking espresso from beakers.

They don’t.

If you're starting from zero, this post is for you. I'm going to walk you through the exact steps to build real, hireable skills—without burning out or wasting months jumping between tutorials. It’s the roadmap I wish someone gave me when I started.

Let’s go.

Step 1: Pick a Focus Area—Don’t Try to Learn Everything

Tech is a buffet, not a one-size-fits-all plate of misery. You don’t need to learn everything—you need to pick a lane.

Here are four great starting points:

  • AI & Data Science – Great if you love solving problems with numbers and logic.
  • No-Code Automation – Perfect for people who like building systems but not typing semicolons.
  • Cybersecurity – For the curious skeptic who loves digital puzzles and spotting weaknesses.
  • Cloud & DevOps – If you like infrastructure, deployment, or bragging about your AWS cert.

💡 Pro tip: Choose based on curiosity, not trends. You’re going to be learning a lot—you might as well enjoy it.

Step 2: Learn the Basics (Without Falling into Tutorial Purgatory)

Now, let’s talk learning.

If you picked a technical path like AI or automation, you will need to learn the basics of programming. But here’s the secret: you don’t need to master it before moving on. Just get comfortable enough to be dangerous.

If you’re going the coding route:

Start with Python. It’s readable, flexible, and used everywhere from AI to automation to back-end dev.
Free beginner resources:

If you’re doing no-code:

Start with tools like:

  • Zapier – for automation
  • Notion + Make.com – for building workflows
  • Airtable – to pretend you're using a database (you kind of are)
  • ChatGPT + AI tools – to build fast, without code

Your Goal: Build mini projects early. Don’t just watch other people code or drag boxes around. Create stuff. Fail early. It’ll hurt less later.

Step 3: Build Projects (Because Tutorials Are Lying to You)

Watching tutorials feels productive. Building projects is productive.

Beginner project ideas:

  • 🧮 Build a personal budget tracker (Python or Airtable)
  • 🤖 Create an AI-powered resume assistant with ChatGPT + Zapier
  • 🔐 Run a phishing detection simulation (for cybersecurity folks)
  • ☁️ Launch a static website on AWS (DevOps intro)

Upload your projects to GitHub or document them on LinkedIn. Show your work. You don’t need to be perfect—just visible.

Step 4: Create Your Learning System (and Stick to It)

Here’s what no one tells you: motivation dies. Systems don’t.

Set up a simple weekly rhythm:

  • 3 hours/week: Learning (video or reading)
  • 2 hours/week: Project work
  • 1 hour/week: Reflect, share, repeat

You don’t need to grind 12 hours a day. You need consistency. Tech rewards people who keep showing up.

Step 5: Get Loud on LinkedIn (No, Seriously)

Document your journey:

  • “Just completed my first AI project using OpenAI’s API!”
  • “Learning Python—any tips from people who’ve done this?”
  • “Tried building a no-code automation today. Here’s what worked.”

This isn’t bragging—it’s marketing. You’re not shouting into the void. You’re building a body of work that says: “Hey recruiters, I’m learning, I’m growing, and I’m serious.”

You’re Not Late. You’re Just Early Compared to Everyone Who Never Starts.

If you’re still reading, good. You’re already ahead of the people who scroll past, panic, and go watch Netflix.

You don’t need a degree. You don’t need perfect grades. You need a plan and the ability to keep showing up.

Whether you’re diving into data science, no-code tools, or full-on AI sorcery, I’ve created a step-by-step roadmap to help you go from confused beginner to job-ready—without wasting time or bouncing between 100 tabs.

👇 Here’s how to get it:

It’s free, actionable, and has helped hundreds of readers avoid the classic “tutorial purgatory” trap.

Next up: In the next post, I’ll show you exactly what projects to build to prove your skills—even if you're still figuring things out. Spoiler: no one cares about your certificate if your GitHub is empty.