LLM and GenAI Interviews 2026 (Practice test with answers)

About this course

Stop bouncing between YouTube tutorials. Start drilling real interview questions.

You know enough to get the AI interview. But do you know enough to pass it?

If you've been rejected from AI/ML/GenAI roles despite months of self-study — you're not alone. The problem isn't your knowledge. It's that no one teaches you the shape of the question interviewers actually ask.

This course fixes that.

What You'll Master Across 6 Practice Tests:

Practice Test 1 — Python Essentials & Prompt Engineering Python fundamentals for AI engineers + designing, explaining, and optimizing prompts for LLM interviews.

Practice Test 2 — Machine Learning & Deep Learning Essentials Probability, statistics, linear algebra, neural networks, backprop, CNNs, and RNNs — the must-know fundamentals asked in every AI round.

Practice Test 3 — LLMs Deep Dive & Fine-Tuning Transformer internals, attention, encoders, decoders, LoRA, QLoRA, PEFT, and fine-tuning trade-offs.

Practice Test 4 — LangChain & LangGraph Mastery Chains, memory, retrievers, tools, graph-based agent flows, and state management — the most-asked frameworks in 2025–26 interviews.

Practice Test 5 — Agentic Patterns & RAG Essentials ReAct, reflection, planning patterns, embeddings, vector stores, hybrid search, re-ranking, and chunking strategies.

Practice Test 6 — LLM Safety, Evaluation & Deployment Hallucinations, jailbreaks, RLHF, guardrails, evals, benchmarks, and production LLM monitoring.

Why This Course Is Different

Reverse-engineered from real 2025–26 hiring loops at Razorpay, Swiggy, Flipkart, Zomato, TCS, Infosys, Wipro, Amazon, Google, Microsoft, Accenture, and Paytm.

Every question has a structured, detailed explanation — not

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