Guides, modèles et outils pour accélérer votre parcours IA. Ressources gratuites construites à partir d'expériences réelles.
Curated paths through our resource library — from beginner to practitioner.
From tokens to transformers: understand how large language models work, how to evaluate them, and how to run them cost-effectively.
Navigate EU AI Act obligations, security red-teaming, and data governance — everything required to deploy AI in regulated environments.
From readiness to roadmap: the complete journey from assessing where you are to building and defending an AI business case.
For engineers: build production AI systems — from MCP and agentic architecture to RAG and data strategy.
Les systèmes d'IA à haut risque doivent être conformes d'ici août 2026. Préparez-vous avec notre guide complet et notre checklist de 47 points.
Nos guides et modèles les plus populaires
The definitive resource for understanding Europe's landmark AI regulation. Covers risk classification, technical requirements, penalties, and step-by-step compliance guidance. Updated for 2026.
25 min read
Lire MaintenantBuild retrieval-augmented generation systems that actually work in production. Covers architecture, chunking, embeddings, vector databases, retrieval strategies, and evaluation frameworks.
35 min read
Lire MaintenantEverything you need to build production AI agents. Covers ReAct, tool-use, and multi-agent architectures. Includes framework comparison (LangGraph, CrewAI, OpenAI Agents SDK), guardrails, evaluation, and deployment patterns.
40 min read
Lire MaintenantThe most comprehensive guide to Large Language Models: tokenization, transformer architecture, attention mechanisms, pretraining, RLHF, DPO, inference sampling, context windows, RAG, open-source models, quantization, and evaluation. 101 through expert.
60 min read
Lire MaintenantEverything about MCP: protocol architecture, transport layers (stdio, HTTP+SSE, Streamable HTTP), tools, resources, prompts, sampling, roots, security model, and full Python/TypeScript server implementation examples.
45 min read
Lire MaintenantProtect your AI systems from prompt injection, jailbreaks, data poisoning, and model theft. Covers OWASP LLM Top 10, adversarial testing methodologies, and defense-in-depth strategies for production AI.
35 min read
Lire MaintenantBuild a bulletproof AI business case. Includes cost modeling framework, ROI projections, risk quantification, stakeholder alignment templates, and a 12-month implementation timeline.
20 min read
Lire MaintenantThe definitive compliance checklist for EU AI Act. Covers system inventory, risk classification, documentation requirements, and implementation timeline. Used by our clients to achieve audit-ready compliance.
Lire MaintenantEverything you need to build production AI agents. Covers ReAct, tool-use, and multi-agent architectures. Includes framework comparison (LangGraph, CrewAI, OpenAI Agents SDK), guardrails, evaluation, and deployment patterns.
The most comprehensive guide to Large Language Models: tokenization, transformer architecture, attention mechanisms, pretraining, RLHF, DPO, inference sampling, context windows, RAG, open-source models, quantization, and evaluation. 101 through expert.
The definitive guide to open source AI: frontier models (Llama, Mistral, Qwen, DeepSeek), training frameworks, fine-tuning with LoRA/QLoRA, inference servers (vLLM, TGI, Ollama), vector databases, orchestration frameworks, and how to choose your stack.
Complete guide to teaching AI models new skills: supervised fine-tuning (SFT), LoRA/QLoRA parameter-efficient adaptation, RLHF, DPO, GRPO, model distillation, model merging (TIES, DARE), dataset preparation, and evaluation frameworks.
Ces ressources fournissent un point de départ. Pour des conseils adaptés à votre situation, parlons-en.