FDE Interview Mastery 200 Beginner to Intermediate Questions

Master LLMs and Generative AI fundamentals — understand how tokens, context windows, temperature, and embeddings actually work under the hood, and confidently explain hallucination, model selection trade-offs, and knowledge cutoffs to customers in real, high-stakes deployment conversations. You will build the kind of foundational fluency that lets you answer the "why" behind unexpected model behaviour, not just the "what."

Develop field-tested prompt engineering skills — go beyond generic tips to master zero-shot, few-shot, and chain-of-thought techniques, diagnose common production prompting failures such as inconsistent or overly verbose outputs, and coach customer teams to write better prompts themselves for more reliable, repeatable results. These are the same techniques used to troubleshoot stalled AI pilots and turn them into production-ready deployments.

Build genuine fluency in Agentic AI — the most in-demand capability customers are asking about right now. Learn the ReAct pattern, tool use, multi-agent orchestration, and human-in-the-loop safeguards so you can scope, design, and confidently defend agentic solutions in front of technical stakeholders. You will also understand common agent failure modes, including infinite loops and reasoning drift, and how to design around them responsibly.

Gain hands-on RAG, integration, deployment, and enterprise knowledge — covering chunking strategies, vector databases, hybrid search, guardrails, evals, latency, and cost optimisation, alongside the responsible AI and compliance landscape that shapes whether enterprise AI projects actually succeed. This includes practical guidance on data privacy, model evaluation, and production monitoring, all reinforced with 200 field-scenario practice questions spanning beginner to intermediate difficulty so you can validate what you have learned against real deployment situations.