Interview Prep Overview

Once you've worked through the topic sections, this is where you drill for the actual interview loop.

• General Coding (DSA) — arrays/strings, trees/graphs, dynamic programming
• ML Coding — implement classical ML, backprop, and attention from scratch
• ML/GenAI Knowledge Q&A — the breadth round, and how to actually prepare for it (the quick-reference drill, plus a 117-question deep dive on RAG specifically)
• Checked question banks: answer, get checked, then read the worked answer. Classical ML, deep learning training, and LLM serving and fine-tuning. For debugging, evaluation and design under load, work through the Specify, Verify, Debug practice track.
• System Design — applying the 9-step framework fluently under time pressure
• Behavioral — STAR method and the stories worth having ready

See the roadmap for the full ordered path through this section.