"Sucking at something is the first step towards being sorta good at something." - JAKE the DOG (Adventure Time)
The Confusing Beginning:
Stepping into the vast realm of Artificial Intelligence (AI), I found myself at a crossroads—overwhelmed yet excited, with a ton of resources at my fingertips and no idea where to begin. YouTube promised a "simple AI project," but the jargons and the underlying concepts lost me midway.
The Structured Approach:
I decided to shift gears. Coursera and Codecademy have been old friends, so I turned to them for clarity.
Google Cloud on Coursera: I've opted for the course on LLMs, starting with 'Introduction to Large Language Models'. Aim? To demystify LLMs and grasp the potential use-cases.
Machine Learning/AI Engineer Career Path on Codecademy: This is where I'll bridge the gaps in my Machine Learning basics. And the cherry on top? Codecademy aids in building a portfolio with tangible projects.
Looking Ahead:
While this is a promising start, I'm cautious. The infamous "tutorial hell" looms large, and I'm determined to avoid it. My strategy is simple: learn just enough to build, iterate, and then move on to the next challenge.
Day 1 down. A world of possibilities awaits. I'll keep you updated on my progress, missteps, and learnings. Stay tuned!
On to Day 2!
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