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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.
10 spots per session maximum — 9 already taken
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30 free minutes with a training advisor — no commitment.
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Les entreprises opérant des systèmes d'IA générative sans monitoring de la qualité des outputs subissent en moyenne 3 incidents de hallucination par semaine impactant les utilisateurs finaux.
Le coût d'inférence LLM non optimisé peut représenter jusqu'à 40% du budget cloud total.
89% des incidents IA critiques auraient pu être détectés 48h avant leur impact avec une observabilité adaptée.
Sans AI SRE structuré, le MTTR (Mean Time To Recovery) des systèmes IA est 6 fois supérieur à celui des applications classiques.
The Formation AI Observability - Fiabilité IA en production à grande échelle 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.
To ensure the quality of the Formation AI Observability - Fiabilité IA en production à grande échelle training, Learni provides the following 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.
The assessment of skills acquired during the Formation AI Observability - Fiabilité IA en production à grande échelle training is carried out through:
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.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Principes de l'AI SRE : SLI, SLO, SLA appliqués aux systèmes d'intelligence artificielle. Error budgets pour les modèles IA : définition, calcul, arbitrage fiabilité vs vélocité. Observability end-to-end : données sources, feature store, model serving, post-inference. Taxonomie des incidents IA : classification, sévérité, processus d'escalation. Étude de cas : post-mortem d'incidents IA dans des organisations à grande échelle.
Observabilité spécifique aux LLM : détection d'hallucinations, toxicité, pertinence. Monitoring des pipelines RAG : qualité du retrieval, cohérence des réponses, latence. Cost observability pour les LLM : token tracking, cache hit ratio, optimisation des prompts. Guardrails en production : filtres automatisés et escalation humaine. Démonstration : plateformes de LLM observability (Langfuse, Helicone, LangSmith).
Construction de runbooks spécifiques aux incidents IA : dérive, dégradation, biais, hallucination. Processus d'incident response : détection, triage, mitigation, recovery, post-mortem. War game immersif : simulation d'un incident IA critique multi-systèmes en temps réel. Automatisation de la remédiation : rollback de modèles, feature flags, circuit breakers IA. Débriefing et retours d'expérience croisés entre participants.
Architecture scalable : monitoring de 10 à 1000 modèles en production. Modèle de coûts et ROI de la plateforme d'AI Observability pour le COMEX. Conformité réglementaire : traçabilité AI Act pour les systèmes à haut risque. Organisation et talent : structurer l'équipe AI Observability et ML Platform. Élaboration du plan de fiabilité IA à 24 mois et soutenance devant le jury.
10 participants max.
$4,840 / per person
4 jours
présentielTarget audience
CTO, Chief AI Officers, VP Engineering, VP Data, directeurs infrastructure, Head of ML Platform et cadres dirigeants C-Level responsables de la fiabilité et de la scalabilité des systèmes IA en production dans leur organisation.
Prerequisites
Expérience significative en direction technique, data engineering ou ML engineering. Connaissance des architectures distribuées et des pipelines MLOps. Familiarité avec les pratiques SRE (Site Reliability Engineering) et les environnements cloud.
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Intermediate
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