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Training Multimodal RAG 2026 - Mastering Advanced Multimodal AIs

Ref: GFA511
10 people max.
4200€ 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
3 journées
distanciel

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Learning objectives

  • Master Multimodal RAG 2026 architectures for certified enterprise applications
  • Develop high-performing hybrid text-image-video retrieval systems
  • Implement multimodal AI agents with advanced state management
  • Optimize multimodal embeddings for increased professional precision
  • Design and deploy scalable RAG pipelines in production
  • Integrate 2026 models like LLaVA or GPT-4V into certified workflows
  • Acquire expert skills in multimodal evaluation and fine-tuning

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 1Multimodal RAG 2026 Fundamentals: text-image integration with hybrid embeddings (CLIP, LLaVA, vector stores)

Dive into the basics of Multimodal RAG 2026 by setting up an expert environment with Hugging Face and LangChain, explore multimodal embeddings via CLIP and BLIP to fuse text and images, perform practical retrieval exercises on real enterprise datasets, build your first multimodal RAG pipeline handling visual queries, test augmented generation with LLaVA on concrete cases, produce a functional prototype with precision metrics, and receive personalized feedback from the trainer.

Module 2Advanced Multimodal RAG 2026 Architectures: hybrid retrieval and AI agents (LlamaIndex, FAISS, reasoning chains)

Build scalable Multimodal RAG 2026 architectures by implementing hybrid vector stores like FAISS and Pinecone to manage videos and documents, develop autonomous AI agents with LangGraph for multimodal reasoning, chain retrieval, reranking, and generation using 2026 models like Gemini 2.0, apply enterprise cases in visual report analysis, optimize chains with tracing tools like LangSmith, generate production-ready deliverables, and evaluate business impact through real simulations.

Module 3Multimodal RAG 2026 Deployment and Optimization: secure production and fine-tuning (Docker, Kubernetes, LoRA)

Scale up by deploying your Multimodal RAG 2026 system with Docker and Kubernetes for high availability, fine-tune expert models via LoRA on confidential enterprise data, integrate security and monitoring with Guardrails and Prometheus, test under real conditions on intensive multimodal workloads, optimize costs and performance for maximum ROI, finalize a complete red thread project with deployed REST API, receive certification, and get an action plan for immediate enterprise integration.

Evaluation method

  • Expert MCQ to validate learning outcomes at the end of the training
  • Continuous evaluation through practical Multimodal RAG exercises
  • Defense of the red thread Multimodal RAG 2026 project before the trainer

Learning method

  • Courses led by an active expert AI trainer
  • Practical exercises on real multimodal enterprise cases
  • Progressive red thread Multimodal RAG project over 3 days
  • Complete course materials and 2026 resources provided to participants

Methods, materials and delivery

The Training Multimodal RAG 2026 - Mastering Advanced Multimodal AIs 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 Multimodal RAG 2026 - Mastering Advanced Multimodal AIs 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 Multimodal RAG 2026 - Mastering Advanced Multimodal AIs 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
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« 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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