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What 6 Years of Pursuing a Degree Really Taught Me
Published 11 days ago • 3 min read
Hi Reader,
Back in 2019, I decided to start a computer science bachelor degree, specializing in Machine Learning and AI. I was 27 at the time, and I felt lucky to find an online program that let me study while keeping my full-time job.
I thought, “Great, I’ll finish it in 3 years.” Fast forward 6 years, with plenty of ups and downs in between, and I’m just now finishing the last module 🥲.
If you asked me today whether I’d do it all over again, I’d hesitate.
On one hand, the degree gave me peace of mind. I scratched the “what if I studied CS?” itch, and discovered things I didn’t even know I didn’t know. For that alone, I have no regrets.
But practically speaking? The tech world today moves so fast. By the time you graduate, half of what you learned feels like ancient history.
Meanwhile, AI is casually rewriting entire job categories while you’re still sweating over big-O notation and automata theory (things you may never need).
I’m not at all against traditional education, especially if it’s a high-quality program. If you’ve got the time, money, and curiosity, and you don’t mind the scenic (but a bit slow) route - go for it!
But if your main goal is to sharpen your technical skills, land a job fast, switch careers, or even simply understand what the heck your technical coworkers are talking about, there are often quicker, more direct paths.
👉 Here are other ways to learn that I've found to pay off quickly:
Diagram created using Claude Artifacts.
1. Learn by solving real problems
Look for friction in your own life. Do you spend time on repetitive, boring tasks? Could you automate them while learning a new tool or skill?
One person I coached built a WhatsApp-like app to handle customer queries for his weight-loss coaching company. The project is challenging for him, but it taught him databases, APIs, RAG pipeline, prompting and front-end basics along the way.
At first, you’ll probably discover you’re missing more foundational skills than you realized. And that’s completely normal.
The good news is, with the right guidance (I’ll share more on that below 👇), you can move much faster than you think.
2. Build domain expertise
Technical skills age quickly. Domain expertise doesn’t.
What you think of as your “non-technical” background might actually be your edge!
Anyone can learn to use Claude or ChatGPT. But fewer people have good judgment - knowing when the AI’s answer is good, when it’s bad, and how to make it better. That comes from real-life experience and expertise.
If you have both domain knowledge AND technical skills, you become a powerful bridge who's able to communicate across teams and add value in any business.
Personally, I think this will matter far more in the long run than knowing every new AI prompting hack.
3. Use AI to accelerate learning
I don't think AI is a full replacement for systematic education - at least not yet. It still misses (a lot of) subtleties. But it can accelerate your learning in ways that save you months.
Here's how I'm currently using AI for learning:
Coding: I use it for targeted tasks, then make manual adjustments when necessary.
Deep research: collecting and transforming data, web search for tooling comparisons and everything tedious.
Creative brainstorming: sometimes I just dump my notes into ChatGPT/ Claude and ask it to expand or organize them in a visual diagram.
For the record, I haven't been able to use AI to write newsletters or script my Youtube videos. So yes, all my posts were written by a human 😉.
If you want to learn how to code, build AI applications from the ground up, and actually understand what’s happening under the hood - I’ve built a program that guides you through all the fundamentals of Python, Machine Learning, and AI.
You’ll join a community of 350+ learners learning to build AI projects, supporting each other, and getting direct access to me along the way.
Grab the 20% ($60)off the full course price until Monday, August 25 👇.
Master data science skills, build awesome portfolios, land the job you love.
Join 6,000+ data professionals who are advancing their careers by learning from real-world projects, gaining first-hand experience, and accessing top resources delivered to your inbox every week.
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