Description:
How feasible is it to learn the necessary skills on my own and find job opportunities in this field? Are there particular challenges I should be aware of before making this big career shift?
4 Answers
The whole idea of “switching” to AI programming without a fancy piece of paper feels like playing chess in a rigged game. The corporations wanting AI talent are less interested in your skillset than how well you can dance to their algorithmic tunes and jargon. Learning on your own is definitely possible, but be ready for the invisible gatekeepers — hiring managers who nod more at pedigree than passion. Plus, the so-called “open source” world they praise? Sometimes it’s another labyrinth designed to chew you up unless you’re already embedded deep inside some elite network. It's not just about coding; it's about decoding the silent handshake rituals behind the scenes in this shadowy tech ecosystem. If you dive in, armor yourself with skepticism toward every "easy path" offered by big tech's recruitment machine.
- Grant Diaz: Thanks for the honest take! Any advice on how to get past those “invisible gatekeepers”?Report
- Anonymous: Hey Grant, glad it resonated. To get past those gatekeepers, focus on building a solid portfolio with real projects—open-source contributions, personal AI projects, or even competitions like Kaggle. Networking is huge too; connect with folks on LinkedIn, attend meetups or virtual AI events, and find mentors who can vouch for your skills. Sometimes a strong recommendation or inside connection can open doors that resumes alone won’t. Stay persistent and keep sharpening both your coding and problem-solving chops. It’s a grind, but doable.Report
You can switch without a degree if you build strong projects and contribute to open source but expect tough competition and need serious self-discipline to keep up with fast AI changes
Switching to AI programming without a formal degree is definitely doable if you embrace remote-first work habits. Prioritize async learning and collaboration so you can absorb concepts deeply on your own schedule, which helps build strong problem-solving skills essential for AI. Focus on outcomes over hours—create tangible projects or contribute to real-world datasets rather than just clocking study time. One helpful tool is using platforms like GitHub combined with project management tools such as Notion or Trello to track your progress asynchronously and showcase your portfolio clearly to employers who value demonstrated impact more than credentials.
Focus on mastering math and algorithms first, then build niche AI projects.
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