AI
Everything about modern AI in one course: LLMs, embeddings, RAG, agents and interview prep.
What Is AI? What Is an LLM?
AI, machine learning, deep learning and large language models, explained with a next-word game you can run.
22 min · Beginner Start lesson AI: One CourseTokens, Context Windows and Cost
Why models read tokens not words, what a context window really is, and how to estimate cost and latency.
20 min · Beginner Start lesson AI: One CoursePrompts, Temperature and Sampling
Roles, system prompts, few-shot examples, chain of thought, and what temperature, top-k and top-p actually do.
24 min · Beginner Start lesson AI: One CourseHallucinations: Why and How to Reduce Them
Why models confidently make things up, the different kinds of hallucination, and a toolbox of fixes.
20 min · Beginner Start lesson AI: One CourseAPIs, SSE, WebSockets and Streaming
How apps talk to models over HTTP, and how streaming works: polling, SSE, WebSockets, with a working parser.
26 min · Intermediate Start lesson AI: One CourseVectors and Embeddings
What a vector is, how text becomes numbers that capture meaning, and how cosine similarity finds related text.
26 min · Intermediate Start lesson AI: One CourseChunking, Vector Databases and ANN Search
How to split documents, store vectors, and search millions of them fast with approximate nearest neighbour indexes.
26 min · Intermediate Start lesson AI: One CourseKeyword Search and BM25
Inverted indexes, TF-IDF and BM25 built from scratch, and why keyword search still beats embeddings for some queries.
24 min · Intermediate Start lesson AI: One CourseHybrid Search and Reranking
Combine keyword and vector search with reciprocal rank fusion, then rerank with a cross-encoder for precision.
24 min · Intermediate Start lesson AI: One CourseRAG: Retrieval-Augmented Generation
The full RAG pipeline end to end, with a working mini-RAG you can run, plus prompt design and common failure modes.
30 min · Intermediate Start lesson AI: One CourseEvaluating and Improving RAG
recall@k, MRR and nDCG computed by hand, faithfulness, chunk-size experiments, and advanced RAG patterns.
26 min · Advanced Start lesson AI: One CourseTool Calling and Structured Output
How a model calls functions: schemas, the request/response loop, validation, parallel calls and error handling.
26 min · Intermediate Start lesson AI: One CourseAgentic AI: From Chatbots to Agents
What an agent really is, the ReAct loop with a runnable demo, workflows vs agents, patterns and failure modes.
30 min · Intermediate Start lesson AI: One CourseThe Agent Harness and Agent SDKs
The code around the model: loop, tools, context, memory, permissions, budgets. Build a mini harness and meet the SDKs.
32 min · Advanced Start lesson AI: One CourseLangGraph, LlamaIndex and LangChain
Graphs as agent control flow (with a mini engine you can run), LlamaIndex's data-first model, and when to use frameworks.
28 min · Advanced Start lesson AI: One CourseMulti-Agent Systems, MCP and AI Safety
Orchestrator-worker and handoff patterns, the Model Context Protocol, prompt injection and defence in depth.
30 min · Advanced Start lesson AI: One CourseShipping AI to Production
Observability, evals, retries, caching, routing, cost control and the architecture of a real streaming AI product.
30 min · Advanced Start lesson AI: One CourseInterview Special I: LLM, Embeddings, RAG and Search Questions
Forty-plus real interview questions with model answers on LLMs, prompting, embeddings, vector search, BM25, hybrid search and RAG.
40 min · Intermediate Start lesson AI: One CourseInterview Special II: Agents, System Design and Live Scenarios
Agent and harness questions, five system design walkthroughs, live debugging scenarios and coding-round exercises.
45 min · Advanced Start lesson AI: One CourseGlossary, Cheat Sheet and Learning Roadmap
Every term from the course in one place, a one-page cheat sheet, and a roadmap for what to learn and build next.
20 min · Beginner Start lesson