LoRA and QLoRA Practical Guide
Most teams cannot full-fine-tune large models for every use case. PEFT methods, especially LoRA and QLoRA, let you adapt behavior with lower memory and cost while preserving operational flexibility.
Adaptation and Retrieval
2 explainers and 1 interview packs. Track your reading and drill this module end-to-end before moving ahead.
Explainers
Concept-first deep dives with practical implementation context.
RAG Pipeline and Retrieval Optimization
Most enterprise GenAI systems are now retrieval-first systems. Teams rarely fail because the generator is weak; they fail because retrieval is noisy, stale, or poorly evaluated. Strong interviews test whether you can reason about retrieval as a data and systems problem, not only as prompt engineering.
Interview Packs
Question banks with layered answers and follow-up ladders.
PEFT and RAG Interview Questions
This file targets high-depth interviews on adaptation strategy, retrieval architecture, and production-safe optimization.