0.1 Series Overview
I take a lot of short DeepLearning.AI-style courses, and the notes from each one used to live in whatever scratch file I had open at the time. This series is where I consolidate them properly instead: one post per course, with the lesson-by-lesson summary, the notebook/code details worth remembering, and a glossary of the terms introduced — written so I (or anyone else) can come back months later and actually use it as a reference.
0.2 Posts in this Series
- 2026-08-27 — Building Adaptive AI Agents — Course Notes — a course on agents that improve from experience across three layers: token-space behavior adaptation (skill induction), token-space knowledge adaptation (code knowledge graphs), and weight-space adaptation (LoRA/QLoRA fine-tuning).
- 2026-08-27 — Building Adaptive AI Agents — Hands-On, Open-Source Edition — the same three lessons, rebuilt with an all-open-source stack (SQLite,
networkx, a local LLM,transformers/peft) and actually run on a real repo, with real output, an interactive graph, and a real LoRA training curve.
Reuse
Citation
BibTeX citation:
@online{goni2026,
author = {Goni, Hasan},
title = {Online {Course} {Notes}},
date = {2026-08-27},
langid = {en}
}
For attribution, please cite this work as:
Goni, Hasan. 2026. “Online Course Notes.” August 27.