Time-boxed path
Learn AI Engineer Free in 6 Months
AI engineering sits on top of real machine learning, so this six-month plan builds the foundation before the frontier. It is 283 hours, about 1.6 hours a day. You start with Python and machine learning, go deep with Andrew Ng's Deep Learning Specialization and Karpathy's from-scratch neural nets, then move into the modern LLM and agent tooling that AI engineering jobs actually use. This is the code-first version of the 30-day AI basics plan: less about prompting, more about building.
The daily math
This plan is 283 hours of free courses spread across 180 days. That works out to about 1.6 hours a day, or roughly 11 hours a week if you prefer to batch it. Miss a day and you make it up on the weekend; the point is a pace you can actually keep.
The plan, course by course
Why this set, and what we left out
We deliberately grounded this in machine learning first, because AI engineers who only know prompting hit a ceiling fast. Karpathy's build-a-neural-net series and Ng's specialization give the depth; Hugging Face's LLM and agents courses cover the applied modern stack. We left pure prompting-heavy material light here since the 30-day AI basics plan already covers it, and we skipped fast.ai to avoid overlapping Ng's specialization.
The honest catch
This plan assumes you will learn Python as its first step, so it is dense. It builds strong ML and LLM foundations, but production AI engineering (serving models, evaluation at scale, infrastructure) is learned on the job after this base.