AI Engineering · 100-level
Open-Source & Sovereignty (India-first)
AIE-1101 creditselectivebadge: open-weightsprereqs: AIE-101
Start this course — free
Earn the open-weights credential
What's inside
Sections & lessons
01
Open-weight families & VRAM math
- The literal GB arithmetic behind 'this model doesn't fit'concept45 min
02
Lab + eval-gate: sovereignty & lock-in
- Naming the exact mechanism holding a stack hostage (Open-Weights badge)concept120 min
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This module's playgrounds
AI Engineering
Next in this path
Where this specialization goes from here — in (level, code) order.
Vocabulary
Key concepts in this course
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Optional · watch & try
Go deeper, elsewhere
Hand-picked public explainers and open tools — always optional, never required, never graded.
What is LoRA? Low-Rank Adaptation for finetuning LLMs EXPLAINEDExplains the low-rank matrix trick that makes LoRA cheap LoRA for fine-tuning LLMs explained with exampleWorked example applying LoRA to an actual model LLM Fine Tuning Explained in 8 Minutes: LoRA, QLoRA, DPOFast comparison of fine-tuning method families · ~8 minHugging Face PEFT — LoRA methodsOfficial reference implementation and guide for LoRA/PEFT fine-tuning LLM Model VRAM Calculator (Hugging Face Space)Estimate GPU memory needed to fine-tune or run a given model at a given quantization
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