Master Your Technology Interview: 1,000+ Real-World Questions & Coding Guides

Start by mastering data structures, algorithms, and system design fundamentals. Then practice with real STAR‑method questions for your target stack (MERN, MEAN, .NET, etc.). Use our curated guides to study 20+ questions per technology, review production‑level code examples, and rehearse behavioral answers with measurable outcomes.

JavaScript/TypeScript (React, Angular, Node.js), Python (AI/ML, data engineering), C#/.NET, and Go remain the most sought‑after. Cloud skills in Azure, AWS, and Kubernetes are equally critical. Generative AI and LLM tooling (LangChain, RAG) are the fastest‑growing categories in job postings.

With focused daily study, most people reach a job‑ready level in 6–12 months. A typical path covers HTML/CSS/JS (4–6 weeks), a front‑end framework like React (4–6 weeks), back‑end with Node.js or .NET (6–8 weeks), databases (4 weeks), and deployment & DevOps basics (2–4 weeks). Our Learning Paths break this down step by step.

STAR stands for Situation, Task, Action, Result. It structures your answer so interviewers can quickly evaluate scope, ownership, technical decisions, and measurable impact. Every behavioral and scenario‑based question on this site uses the STAR format with concrete metrics, making it easy to adapt answers to your own experience.

Yes — even if you don't become an ML engineer. Understanding prompt engineering, RAG architectures, and how to integrate LLM APIs into existing apps is now a baseline expectation for senior roles. Our AI/ML interview guides and GenAI question banks cover exactly what hiring managers test for, without requiring a PhD.