🎁Azure · AWS · Google — 1 free certification per learner, up to $400.Get the offer →
← Back

Training Corrective RAG - Eliminate LLM Hallucinations in Production

Ref: KLA293
10 people max.
7000€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

Share in 2 clicks

EquansAptarArcelorMittalUbisoftINSEECLa PlateformeCESIEFREIEPSIINGETISMy Digital SchoolYnovEquansAptarArcelorMittalUbisoftINSEECLa PlateformeCESIEFREIEPSIINGETISMy Digital SchoolYnov

Learning objectives

  • Master Corrective RAG for reliable responses in professional contexts
  • Develop retrieval correction techniques to optimize accuracy
  • Implement generative correction in certifying LLM pipelines
  • Design scalable Corrective RAG systems for the enterprise
  • Optimize RAG performance with automated skill evaluation
  • Deploy Corrective RAG solutions in secure production

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Fundamentals of Corrective RAG: Diagnose weaknesses in RAG pipelines (LangChain, audit tools)

In-depth analysis of classic limitations of RAG systems, identification of hallucinations via automated audits with RAGAS and TruLens, hands-on with Corrective RAG to correct retrieval in real-time, practical exercises on real enterprise datasets, creation of a first corrective pipeline with immediate trainer feedback, production of a personal diagnostic report.

Module 2Retrieval Correction in Corrective RAG: Refine embeddings and queries (vector stores, reranking)

Exploration of advanced self-correction techniques on retrieval, implementation of hybrid rerankers with ColBERT and cross-encoders, optimization of dynamic embeddings via FAISS and Pinecone, real enterprise cases on large knowledge bases, development of a testable corrective module, validation by precision/recall metrics, delivery of a refined prototype ready for integration.

Module 3Generative Correction in Corrective RAG: Integrate factual verification (LLM judges, grounding)

Deployment of post-generation correction mechanisms with LLM-as-judge, setup of dynamic grounding against reliable sources, training of internal critics for self-correction, exercises on critical scenarios like medical or legal Q&A, use of tools like Guardrails and NeMo Guardrails, implementation of a complete Corrective RAG workflow, evaluation by personalized benchmarks.

Module 4Advanced Corrective RAG Architecture: Scale for the enterprise (orchestration, monitoring)

Design of modular Corrective RAG architectures with LangGraph and Haystack, integration of real-time monitoring via Prometheus and LangSmith, management of multi-agent workflows for collaborative corrections, enterprise use cases on chatbots and virtual assistants, development of a system resilient to prompt injection attacks, load testing and GPU cost optimization, production of a deployable blueprint.

Module 5Deployment and Optimization of Corrective RAG: Secure production (CI/CD, final evaluation)

Production deployment with Docker, Kubernetes, and FastAPI for Corrective RAG pipelines, CI/CD setup via GitHub Actions for continuous updates, holistic evaluation by A/B testing and human evaluation, resolution of real challenges like latency and token cost, finalization of the red thread project with expert code review, preparation for skill certification, delivery of resources for autonomous maintenance.

Evaluation method

  • Multiple-choice quiz to validate acquired knowledge at the end of the training
  • Continuous evaluation through practical exercises
  • Defense of the red thread project in front of the trainer

Learning method

  • Courses led by an active expert trainer
  • Practical exercises on real business cases
  • Progressive red thread project throughout the training
  • Complete course materials provided to each participant

Methods, materials and delivery

The Training Corrective RAG - Eliminate LLM Hallucinations in Production program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training Corrective RAG - Eliminate LLM Hallucinations in Production program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training Corrective RAG - Eliminate LLM Hallucinations in Production program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

Your professional training, anywhere

Let's build
your next
program.

30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.

Reply within 24 h · Industry-certified · Corporate funding
WhatsApp