139 Gen AI Interview Questions with answers with Ritesh Sinha

Data Science & GenAI Interview Questions — Decoded

Stop prepping from scattered PDFs and outdated question banks. This ebook is a compilation of 139 real questions asked across recent Data Science, GenAI, and Agentic AI interview rounds — the kind of questions actually being asked right now, not recycled theory.

Every question comes with a clear, structured answer you can actually use — not just a definition, but the reasoning an interviewer wants to hear.

What's inside:

• Classical ML & Statistics (36 Qs) — imbalanced data, evaluation metrics, PCA, Random Forest, bias-variance, p-values, and more
• GenAI & LLM Fundamentals (42 Qs) — RAG architecture, transformers, embeddings, chunking, hallucination control, fine-tuning (LoRA), prompt engineering
• Agentic AI, LangGraph & ADK (20 Qs) — state graphs, router agents, supervisor-worker patterns, grounding, tool-calling
• Cloud, GCP & Deployment (18 Qs) — CI/CD, Docker, GKE, Vertex AI, RAG Engine, observability
• Python & Coding (13 Qs) — with working code for every problem
• Behavioral & Career (10 Qs) — how to actually answer the "soft" questions that decide close calls

Why this is different:

Most interview prep content is generic. This is sourced from real ongoing interview rounds for Data Science, GenAI Engineer, and Agentic AI roles — so you're prepping for what's actually being asked, not what was asked three years ago.

Format: PDF, print-ready, yours to keep and revisit before every round.