AI Concepts for Beginners: 19 Core Concepts Explained Simply

The AI concepts every beginner needs, in learning order: start with AI, LLMs and prompts, then move to RAG, embeddings, AI agents and MCP. Each guide is free and ends with a quick quiz.

19 free concept guides

Level 1: AI Basics

What AI, LLMs and prompts are, in simple words.

01AIAI (artificial intelligence) is the ability of a computer to do tasks that normally need human intelligence, such as understanding language, recognising faces, making predictions and taking decisions.16 min read 02AI vs ML vs DLAI is the broad goal of making machines act intelligently.14 min read 03Generative AIGenerative AI is a type of artificial intelligence that creates new content, such as text, images, audio, video and code, instead of only sorting or predicting labels.15 min read 04LLMIn AI, LLM stands for Large Language Model: an AI model trained on huge amounts of text to understand and generate human language.15 min read 05Neural NetworkA neural network is a type of machine learning model made of layers of small connected units called neurons.15 min read 06Prompt EngineeringPrompt engineering is the skill of writing clear instructions (prompts) so an AI model like ChatGPT, Claude or Gemini gives accurate, useful answers.16 min read 07AI TokensTokens are the small chunks of text that AI language models read and write, such as a whole word, part of a word, a space or a punctuation mark.17 min read 08AI HallucinationAI hallucination is when an AI model such as ChatGPT, Claude or Gemini produces information that sounds confident and correct but is false or made up, like fake facts, quotes, citations or code libraries.16 min read

Level 2: Builder Concepts

How RAG, embeddings, agents and MCP actually work.

09Context WindowA context window is the maximum amount of text a large language model can read and work with at one time, measured in tokens.16 min read 10RAGRAG (Retrieval-Augmented Generation) is a technique where an AI model first searches a trusted set of documents for relevant information, then uses those passages to write its answer.16 min read 11EmbeddingsEmbeddings are lists of numbers (vectors) that represent the meaning of text, images or other data, so that similar things get similar numbers.16 min read 12Vector DatabaseA vector database is a database built to store embeddings (lists of numbers that capture meaning) and quickly find the ones most similar to a query.16 min read 13Fine-TuningFine-tuning is the process of taking a model that is already trained on huge general data, such as an LLM, and training it a little more on a smaller set of your own examples.16 min read 14RAG vs Fine-TuningRAG (retrieval-augmented generation) gives an AI model the right documents to read at answer time, while fine-tuning trains the model on examples so its behaviour changes permanently.14 min read 15AI AgentAn AI agent is an AI system that works toward a goal by deciding its own steps and taking actions with tools, such as searching the web, running code or filling a form.16 min read 16MCPMCP (Model Context Protocol) is an open standard that lets AI apps like Claude, ChatGPT and Cursor connect to outside tools and data through one common interface.16 min read

Level 3: Advanced

The architecture behind modern models and agentic systems.

17AI Agents vs Agentic AIAn AI agent is a specific system: a language model that uses tools in a loop to finish a task.16 min read 18Transformer ModelA transformer model is a neural network architecture that processes all the words in a text at once and uses a technique called attention to decide which words matter to each other.16 min read 19Attention MechanismAttention in an LLM is the mechanism that lets each token look at every other token in the input and decide how much each one matters to its meaning.17 min read

In the Unrot AI app

Practise every concept in 5-minute interactive lessons.

Interactive lessons
Progress tracking
Daily streaks
Certificates
Daily AI news

AI concepts: frequently asked questions

What are the basic AI concepts for beginners?

The basic AI concepts are artificial intelligence, machine learning, deep learning, generative AI, large language models (LLMs), tokens and prompts. Together they explain what tools like ChatGPT, Gemini and Claude are and how they produce answers.

Which AI concepts should I learn first?

Start with what AI is, AI vs ML vs deep learning, generative AI and LLMs. Then learn prompts, tokens, context windows and hallucination. After that, move to RAG, embeddings, fine-tuning, AI agents and MCP.

What AI concepts are asked in interviews?

Interviewers most often ask about LLMs, tokens, context windows, hallucination, RAG, embeddings, fine-tuning versus RAG, and AI agents. Our AI interview prep section has role-wise questions with model answers.

Are these AI concept guides free?

Yes. Every guide on this page is free to read with no sign-up. The Unrot AI app is free to start if you want interactive lessons, progress tracking, streaks and certificates.

Can I learn AI concepts in Hindi?

Yes. Every concept guide includes a simple Hindi meaning, and our AI glossary has a page of common AI terms explained in Hindi and Hinglish.

Explore more free AI guides

Interview PrepAI interview questions with model answers17 roles AI GlossaryA to Z AI terms in plain words19 terms AI ProjectsProject ideas and step-by-step builds17 guides Learning PathsFree week-by-week AI paths by role16 paths Best ResourcesHonest lists of courses, apps and books15 lists