Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Formation Agentic RAG - Agents IA autonomes puissants training are: Maîtrise avancée de Python, expérience en RAG et LLMs, utilisation de frameworks comme LangChain ou LlamaIndex, notions de workflows multi-agents. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Formation Agentic RAG - Agents IA autonomes puissants training is available in présentiel. The format can be adapted to your needs (inter, intra, custom).

Formation Agentic RAG - Agents IA autonomes… | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Formation Agentic RAG - Agents IA autonomes puissants training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Formation Agentic RAG - Agents IA autonomes puissants training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Formation Agentic RAG - Agents IA autonomes puissants training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training objectives

Maîtriser les architectures Agentic RAG pour applications professionnelles certifiantes

Concevoir des agents autonomes intelligents en formation enterprise

Optimiser les pipelines RAG avec outils avancés pour compétences scalables

Implémenter des workflows multi-agents robustes et sécurisés

Déployer des solutions Agentic RAG en production d'entreprise

Évaluer les performances pour une montée en compétences certifiante

Training program

Module 1Fondamentaux Agentic RAG : architectures avancées et outils (LangGraph, CrewAI)

Découvrez les principes avancés d'Agentic RAG via des cas concrets d'entreprise, implémentez des agents autonomes avec LangGraph pour raisonner en étapes, configurez des outils de routing intelligents, réalisez des exercices pratiques sur datasets réels, produisez un premier workflow fonctionnel testé en groupe, intégrez des LLMs comme GPT-4 pour des réponses contextualisées précises.

Module 2Pipelines Agentic RAG : optimisation et multi-agents (LlamaIndex, AutoGen)

Plongez dans l'optimisation des pipelines RAG agentiques, utilisez LlamaIndex pour indexer vectoriellement des corpus massifs, déployez des multi-agents collaboratifs avec AutoGen, testez des scénarios de décision autonome, analysez les bottlenecks via profiling tools, générez des livrables comme un dashboard de monitoring, appliquez des techniques de fine-tuning pour booster les performances en contexte professionnel.

Module 3Sécurité et scalabilité Agentic RAG : déploiement enterprise (Kubernetes, Guardrails)

Approfondissez la sécurisation des agents RAG avec Guardrails pour valider les outputs, intégrez des mécanismes de privacy comme RAG hybride, scalez sur Kubernetes pour charges élevées, simulez des attaques prompt injection, développez des agents résilients avec retry logic, produisez un blueprint de déploiement cloud-ready, validez via stress-tests en conditions réelles d'entreprise certifiante.

Module 4Projets avancés Agentic RAG : cas réels et évaluation (projet final certifiant)

Réunissez toutes les compétences en un projet capstone sur un use-case enterprise comme assistant virtuel intelligent, intégrez outils vus pour un système complet multi-agents, optimisez les métriques RAGAS pour précision, présentez votre livrable en pitch professionnel, recevez feedback personnalisé des experts, obtenez une certification Qualiopi validant vos compétences avancées en Agentic RAG.