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Training Corrective RAG - Eliminate AI Hallucinations

Ref: IJD498
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

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Learning objectives

  • Master corrective RAG mechanisms for precise responses in production
  • Develop skills in detecting and correcting professional AI hallucinations
  • Implement scalable corrective RAG pipelines for certifying enterprises
  • Optimize retrieval and generation with advanced self-corrective techniques
  • Design robust RAG systems integrating feedback loops and reranking
  • Deploy high-performance corrective RAG applications in enterprise environments

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.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Diagnosis: Identify RAG weaknesses and corrective RAG basics (analysis tools, metrics)

In-depth analysis of common RAG failures such as hallucinations and imprecise retrieval, hands-on with diagnostic tools (RAGAS, DeepEval, TruLens), evaluation of existing pipelines on real enterprise datasets, practical exercises to quantify errors using metrics like faithfulness and answer relevance, development of an initial diagnostic report applied to your red thread project, immediately highlighting potential precision gains.

Module 2Fundamentals: Implement basic correction in corrective RAG (self-reflection, critique tokens)

Immersion in self-reflective techniques for RAG, configuration of critic models (GPT-4o, Llama-3) for self-evaluating responses, development of adaptive prompts to correct semantic drifts, practical workshops on LangChain to integrate reflection loops, tests on concrete enterprise cases such as customer chatbots, production of a functional corrective RAG prototype boosting reliability by 40%, with personalized code review by the trainer.

Module 3Advanced: Reranking and hybrid retrieval in corrective RAG (Cohere Rerank, ColBERT, ensembles)

Exploration of advanced rerankers to refine retrieval, integration of Cohere Rerank and hybrid ColBERT models into RAG pipelines, optimization of embeddings with corrective fine-tuning, exercises on massive datasets simulating enterprise loads, implementation of retrieval ensembles to minimize false positives, development of a deployable reranking module for your project, demonstrating precision gains up to 60% in real conditions.

Module 4Optimization: Feedback loops and scaling corrective RAG (active learning, distillation)

Design of human-AI feedback loops to iterate on corrective RAG, implementation of active learning with tools like Argilla, knowledge distillation for lightweight models, horizontal scaling via vector stores (Pinecone, Weaviate) with dynamic corrections, practical workshops on high-load enterprise scenarios, development of a self-improving system on the red thread project, proving a 50% reduction in operational costs while maintaining professional expertise.

Module 5Deployment: Production and monitoring of corrective RAG (observability, A/B testing)

Production deployment of corrective RAG pipelines with Docker and Kubernetes, setup of monitoring (Prometheus, LangSmith) to track drifts in real-time, comparative A/B testing on business metrics, securing against prompt injection attacks, finalization of the red thread project with complete deliverables (code, dashboard, report), certification session via enterprise scenario simulation, ensuring immediate integration and rapid ROI.

Evaluation method

  • Expert-level multiple-choice quiz on corrective RAG metrics and advanced techniques
  • Practical evaluation through development of a custom pipeline
  • Red thread project presentation with certifying trainer audit

Learning method

  • Live sessions led by production-experienced AI expert trainer
  • Hands-on exercises on authentic enterprise cases
  • Evolving red thread project across 5 days
  • Complete resources (code, notebooks) provided

Methods, materials and delivery

The Training Corrective RAG - Eliminate AI Hallucinations 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 AI Hallucinations 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 AI Hallucinations 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.

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