Mastering AI and machine learning, one step at a time.
Every great journey needs a roadmap. Learning AI and machine learning will take effort and discipline, but without a clear plan, it’s easy to get lost. The last thing I want is to end up stuck in what so many self-taught coders face: tutorial hell, that endless loop of watching course after course without ever building anything real.
To avoid that, I focus on two principles:
Have a clear framework for how I will learn AI.
Always put knowledge into practice, either by building a project after each course or by creating detailed notes I can share with you.
After some research (and with the help of AI), here is the framework I’ve chosen:
Level I: Learning how to build with AI
Using tools like Cursor, Lovable, Windsurf, and workflow builders like n8n to accelerate coding and automate workflows.Level II: Learning how to build things that use AI
Creating GPT wrappers, apps, and full-stack projects that interact with foundational model APIs.Level III: Learning how to build AI itself
Digging into the fundamentals of training and developing foundational models.
Is this the perfect framework? Maybe not, but it strikes the right balance of clarity and simplicity for me, which is exactly what I need right now to move forward.
To make sure I put every lesson into action, I will also be tracking my progress in a structured way using Google Sheets:
Pay special attention to the final column, Project/Outcome, where I commit to turning each completed course into something tangible.
And with that, the journey begins.
