Tutorials
AI learning tutorials from beginner to advanced to help you master LLM development systematically.
Featured Tutorials
Getting Started with LLMs: How Large Language Models Work
A plain-language explanation of how large language models (LLMs) work: tokens, next-word prediction, the context window, and hallucination.
Prompt Engineering in Practice: Writing High-Quality AI Prompts
Master the core techniques of prompt engineering: clear instructions, context and examples, step-by-step reasoning, role setting, and common pitfalls.
Build Your First AI App with the OpenAI API
From obtaining an API key to sending your first chat request and handling streaming output and errors—walk through the full OpenAI API flow.
Build a Knowledge-Base Q&A System with RAG
Understand the full retrieval-augmented generation (RAG) flow: document chunking, embeddings, vector retrieval, and context assembly so the LLM answers from your knowledge base.
Getting Started with Fine-Tuning: LoRA and QLoRA
Understand when fine-tuning is needed, and the core ideas and practical tips behind the efficient fine-tuning methods LoRA and QLoRA.
Deploying Open-Source LLMs Locally: Ollama in Practice
Run open-source LLMs locally with a single command using Ollama, covering installation, running, API access, and model selection.
Building AI Agents in 2026: From Chatbots to Autonomous Systems
Agentic AI is the defining trend of 2026. Learn how AI agents plan, use tools, and act autonomously — the agent loop, function calling, MCP, frameworks, and safety guardrails.
Best AI Coding Agents in 2026: Claude Code vs Cursor vs Copilot vs Codex
A practical 2026 comparison of the top AI coding tools — GitHub Copilot, Cursor, Claude Code, and OpenAI Codex — by how they work, their strengths, and which to choose.
Getting Started with MCP: The Universal Standard for AI Tool Integration
Learn what the Model Context Protocol (MCP) is, why it matters in 2026, and how to connect AI models to external tools and data sources through a single, open standard.
Vibe Coding in Practice: Building Apps by Describing What You Want
A practical guide to vibe coding — the 2026 workflow where you describe your app in natural language and let AI coding agents build it, iterate, and debug.
Multimodal AI in Practice: Building with Vision, Audio, and Video Models
Learn how to combine vision, audio, and video AI models into real applications — from image understanding and speech synthesis to video generation.
AI Workflow Automation: Connecting Models, Tools, and Data Pipelines
A practical guide to building automated AI workflows with low-code platforms (Dify, n8n, Flowise) and orchestration frameworks (LangChain, LangGraph, CrewAI).
More Learning Resources
The Complete OpenAI API Guide
A comprehensive, step-by-step guide to the OpenAI API ecosystem, covering GPT, DALL·E, and Whisper models in depth. It walks you through account setup, authentication, making your first API call, prompt design patterns, and cost optimisation strategies—ideal for developers new to the OpenAI platform who want a structured learning path.
LangChain Framework Tutorial
An in-depth tutorial on the LangChain framework, walking through its architecture and core modules—Chains, Agents, and Memory—with hands-on examples. It also covers RAG integration, custom tool development, and debugging strategies, making it a solid starting point for developers ready to move beyond simple prompts and build production-grade LLM applications.
Prompt Engineering Guide
A widely recognised, community-driven resource that systematically teaches prompt engineering — from foundational techniques like zero-shot and few-shot prompting to advanced methods such as chain-of-thought reasoning. It includes multilingual examples, model-agnostic design principles, and practical tips that help practitioners at every level improve AI output quality in a structured way.
Whisper Speech Recognition Tutorial
OpenAI's open-source speech recognition model, Whisper, trained on a large and diverse multilingual dataset. It can transcribe speech in roughly 99 languages and translate any language directly into English — all runnable locally without external services. Ideal for developers who need accurate, privacy-friendly speech-to-text, subtitle generation, or voice-search indexing.
Hands-on LLM Fine-Tuning
A practical, hands-on guide to fine-tuning large language models, covering parameter-efficient approaches like LoRA and QLoRA alongside traditional full fine-tuning. It walks through dataset preparation, hyperparameter tuning, and evaluation metrics with real code examples. Aimed at ML engineers who want to adapt base models to specific domains without the cost of training from scratch.
OpenAI Whisper Speech Recognition Guide
Official documentation for OpenAI Whisper, the open-source speech recognition model trained on diverse multilingual audio. It covers installation, model size selection, and transcription API usage, with support for roughly 99 languages and direct translation to English. Aimed at developers who need accurate, locally runnable speech-to-text for subtitling, meeting notes, or voice search indexing.
The Complete Midjourney Guide
A comprehensive guide to Midjourney V6, walking through the full image generation workflow from prompt structure to parameter usage like stylize, chaos, and quality. It covers advanced techniques such as image blending, style references, and the remix feature, with practical examples throughout. Ideal for intermediate creators who want to harness the latest model capabilities for consistent, high-quality results.
Python AI/ML Libraries Collection
A curated roundup of the most widely used Python libraries for AI and machine learning, covering deep learning frameworks like TensorFlow and PyTorch, classical ML with Scikit-learn, data manipulation with NumPy and Pandas, and emerging tools for LLM integration. Each entry includes a brief description, typical use case, and installation command — a handy reference for practitioners building their ML toolkit.
Stable Diffusion Beginner Tutorial
A beginner-friendly guide to Stable Diffusion, the open-source text-to-image model. It walks through environment setup, model selection, and core generation workflows, explaining key concepts like sampling steps, CFG scale, and seed control. With practical tips and common troubleshooting advice, it is a solid starting point for anyone curious about AI image generation but unsure where to begin.
Replicate API Usage Guide
A step-by-step tutorial on using the Replicate API to run thousands of open-source AI models for image, video, audio, and text tasks. It covers account setup, making your first prediction, understanding pricing, and optimising for cold starts. Ideal for developers who want to experiment with diverse models without committing to GPU infrastructure.
Hugging Face Transformers Tutorial
The official tutorial for Hugging Face Transformers, the industry-standard library for NLP and computer vision. It covers text classification, tokenisation, translation, image segmentation, and more, with code examples for both PyTorch and TensorFlow backends. Aimed at practitioners who want to leverage pre-trained models or fine-tune them on custom datasets for production use.
LlamaIndex Framework Tutorial
A hands-on tutorial for LlamaIndex, the framework designed for building RAG applications that connect LLMs to custom data sources. It covers data ingestion pipelines, indexing strategies, query engines, and agent-based retrieval, with practical examples for PDF, web, and database connectors. Aimed at developers who want to build domain-specific AI assistants grounded in their own documents.
Flux Image Generation Model Guide
FLUX is a family of open-source image generation models known for strong prompt adherence and high visual quality. This guide covers the different FLUX variants, prompting techniques for better results, and where to run them — locally on consumer GPUs or via hosted API services.
DeepSeek API Usage Guide
DeepSeek provides high-performance chat and reasoning models at remarkably low cost, with an OpenAI-compatible API that makes migration trivial. This guide walks through setup, key endpoints, and best practices for getting the most out of DeepSeek's strong coding and math capabilities.
ComfyUI Workflow Guide
ComfyUI uses a node-based visual workflow system that gives you precise control over every step of image generation. This guide walks through building workflows from scratch, using reusable shareable graphs, and advanced techniques like inpainting and upscaling for production-quality results.
Suno AI Music Creation Guide
Suno is an AI music generation platform that creates complete songs with vocals and instruments from text prompts. This guide covers prompting techniques for genres, moods, and song structure, how to use custom lyrics, and practical tips for getting better vocal quality and mixes.
Cursor IDE Usage Guide
Cursor is an AI-native code editor built as a VS Code fork, offering deep codebase awareness with Composer for multi-file edits, context-aware chat, and smart autocomplete. This guide covers setup, key workflows, and tips for getting the most out of Cursor's polished AI editing experience.
Runway Video Generation Guide
Runway is a leading AI video generation platform offering text-to-video and image-to-video workflows with motion and camera controls. This guide covers practical techniques for creating high-quality clips, refining motion, and stitching short AI-generated segments into longer polished sequences.
Learn Prompting Tutorial
Learn Prompting is a free, open-source course that systematically teaches prompt engineering from foundational techniques to advanced strategies like chain-of-thought and few-shot learning. It covers text, image, and code generation prompts, making it a comprehensive resource for anyone looking to get better results from AI models.
fast.ai Practical Deep Learning Course
fast.ai offers a free, practical deep learning course that uses a top-down teaching approach — building working models first, then diving into theory. It covers computer vision, NLP, and tabular data, with hands-on notebooks that let developers start training real models from day one.
OpenAI Cookbook
The OpenAI Cookbook is the official collection of example code and practical guides for building with the OpenAI API. It covers real-world patterns from embeddings and RAG to function calling and fine-tuning, with runnable notebooks that developers can adapt directly into production applications.
Google Machine Learning Crash Course
Google's Machine Learning Crash Course is a free, hands-on introduction to machine learning featuring video lessons, interactive visualizations, and coding exercises with real datasets. It covers core concepts from linear regression to neural networks, making it an ideal starting point for developers new to ML.