30 days of gamified AI prep, live interview practice, and a real RAG capstone

Real numbers

600+ interview questions with answers. 105 recall cards and 42 hands-on code labs. Learners sign in from 7+ countries.

The problem

You've watched the tutorials, and the interview still feels like a coin flip. Another Udemy course at 2am, a four-hour YouTube video you never finished, one more certificate for a LinkedIn profile nobody reads. Watching feels like progress. Then a real interviewer asks "why?" and none of it is there.

The interview math is simple: recall × build × rehearse = the offer

It multiplies. Struggle on any one and the other two can't carry you. Watching tutorials trains none of the three. A little of each, every day, for 30 days. That's the whole method.

Three moves, repeated until it's automatic

Learn by retrieving

You don't re-read. You retrieve. Every concept opens on a question; answer in your head, then flip and an AI grades you in your own words. Spaced repetition schedules the next hit, and each card opens into a full deep dive.

Build it by hand

An in-browser Python IDE takes you from the basics all the way to a deployment capstone, from a softmax to a LangChain RAG chain, with zero local setup.

Rehearse out loud

AI voice mock interviews put you on the spot and score your answers in real time, on quick daily drills or a full timed mock, the way the real room works.

Four tools, one platform

• Active-recall cards with an AI tutor and deep dives. Retrieve the answer, get AI-graded, and let spaced repetition schedule the next review.
• Code arena, a built-in Python IDE. Read the problem, write the solution, run live tests. Build real things by hand, from a softmax to a RAG chain.
• Live voice mock interviews: speak your answers to an AI interviewer, scored and corrected in real time. You can watch a recorded session on the site before you try one.
• A real RAG capstone, a 5-part project on a live LangChain kernel: build retrieval, add agents (LangGraph, MCP), make it trustworthy with evals, and ship it with FastAPI. A real project you can talk through in any interview.

Foundations → Applied → Advanced. In order.

Foundations, free forever: how LLMs work under the hood. Text becomes tokens, tokens become vectors, vectors become predictions. It's the real platform.

Applied (₹1,499): turn the fundamentals into working systems. Attention at scale, RAG, tool use, and how to evaluate what you build. Includes 2 AI voice interviews plus unlimited tailored interview drills.

Advanced (₹2,999): ship it. Quantization, efficient serving, deployment, and the systems-design thinking interviews probe hardest. Includes 5 AI voice interviews, unlimited tailored drills, and real-gap interview question banks.

The questions that end interviews. You'll have answers.

• The retriever finds the right doc but the model still hallucinates. What do you check? (chunking, reranking, context order, grounding)
• RAG vs fine-tuning vs long-context. When do you reach for which?
• How do you evaluate a RAG system with no ground-truth labels? (LLM-as-judge, RAGAS, faithfulness)
• Walk me through a tool-calling agent, and where it breaks. (tool-calling, LangGraph, MCP, agent memory)

Before you commit

Is AI engineering still hiring? Demand still outruns supply for people who can actually build. Employers want a shipped RAG or agent project, not one more certificate. This is applied engineering, if you can write Python you're in.

You can keep grinding tutorials on your own. Or start free tonight: Foundations is free forever, the real platform. Go deeper with Applied, Advanced or Self-Paced when you're ready. No lock-in, no sales call.

Explore the full walkthrough →