30 units, 410 lessons, 2,084+ questions.
Everything you need for senior+ engineering interviews.
Master databases, caching, scaling, APIs, and distributed systems.
Every system starts with data. Master storage before anything else.
The fastest request is the one you don't make. Master caching to 10x performance.
One server is never enough. Learn to distribute load across thousands of machines.
Services don't exist in isolation. Master how they talk to each other.
The hardest problems in computer science. Master consensus, consistency, and failure.
From ML foundations to LLM engineering, agents, and production safety.
Every ML interview starts here. Master the fundamentals that separate junior from senior candidates.
Neural networks power modern AI. Build the foundation for understanding transformers.
Transformers changed everything. Master the architecture that powers modern AI.
The full lifecycle from pre-training through post-training to inference optimization. Scaling laws, RLHF pipelines, KV caching, and prompt caching economics.
Building applications with LLMs is the fastest-growing area in AI. Master RAG, embeddings, and fine-tuning.
You cannot improve what you cannot measure. Master evaluation frameworks, benchmarks, and testing for ML and LLM systems.
From prompts to production chatbots. Master system design, context engineering, adaptation strategies, and structured output.
Ground LLMs in real data. Master document parsing, hybrid retrieval, RAFT, and end-to-end RAG operations.
The complete guide to building AI agents. From foundational autonomy concepts and workflow patterns to function calling, agent architectures, multi-agent coordination, reliability engineering, and computer use.
Inference-time scaling, chain-of-thought, tree of thoughts, reward modeling, and deep research pipelines.
From text-to-image to text-to-video. Diffusion models, DiT architectures, evaluation metrics, and responsible generation.
Ship ML systems that work at scale. MLOps, caching, routing, observability, prompt injection defense, and AI governance.
JS internals, TypeScript, React patterns, and the modern frontend ecosystem.
Every frontend interview starts here. This separates devs who use JS from devs who understand JS.
Async patterns, modules, generators, and the runtime details interviewers love to ask about.
TypeScript is now table-stakes for senior roles. Master the type system that powers modern frontend.
The heart of frontend interviews. Hooks, rendering, data fetching, forms, and the component model.
What separates senior from staff React engineers. Performance, React Compiler, Server Components, Next.js, and React Native.
Data model, OOP, concurrency, async, and production Python.
"Everything is an object." Understand Python's data model and you understand Python.
Knowing when to use what, and why dict lookups are O(1). The algorithmic backbone of Python interviews.
Python's unique take on OOP: MRO, descriptors, metaclasses, and decorators.
"Explain the GIL" is asked in virtually every senior Python interview. Master threads, processes, and asyncio.
What makes a Python developer production-ready. Testing, profiling, type hints, and CPython internals.
End-to-end system design walkthroughs with deep-dive questions.
End-to-end system design interview walkthrough. Architecture, memory, planning, tools, safety, and evaluation for an AI personal assistant.
End-to-end system design interview walkthrough. Data curation, tokenization, distributed training, fault tolerance, scaling laws, and evaluation for pre-training a large language model.
End-to-end system design interview walkthrough. URL frontier management, async fetching, headless rendering, deduplication with Bloom filters and SimHash, politeness policies, storage at petabyte scale, and adaptive re-crawling strategies.