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Training Multimodal RAG - Deploying Multimodal AIs 2026

Ref: APL798
10 people max.
5600€ 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
4 journées
distanciel

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Learning objectives

  • Master Multimodal RAG architectures for professional certifying applications
  • Develop RAG pipelines integrating text, images, and audio in enterprise settings
  • Implement multimodal embeddings with 2026 models like CLIP-ViT
  • Optimize retrieval and generation for scalable performance
  • Design secure and production-deployable Multimodal RAG systems
  • Evaluate and fine-tune models for concrete business cases
  • Acquire expert skills in Multimodal RAG for Qualiopi certification

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 1Fundamentals: 2026 Multimodal RAG architectures (embeddings, hybrid vector stores)

Dive into 2026 Multimodal RAG advancements by setting up expert environments with Hugging Face and Pinecone, generate multimodal embeddings unifying text and images via CLIP-ViT-Large, configure hybrid vector databases for cross-modal retrieval, complete exercises on real enterprise datasets like multimedia product catalogs, produce your first functional multimodal RAG prototype with immediate trainer feedback for instant professional mastery.

Module 2Pipelines: Implementing Multimodal RAG with LangChain and LlamaIndex (modal fusion)

Build advanced Multimodal RAG pipelines integrating LangChain for retrieval-generation chaining, fuse modalities via LlamaIndex and models like BLIP-2 for audio-visual, test on concrete enterprise virtual assistant cases analyzing PDF documents with photos, optimize hybrid queries for enhanced precision, develop a multimodal reranking module, validate through practical exercises on red thread projects, deliver a robust RAG system ready for production scaling.

Module 3Optimization: Fine-tuning 2026 Multimodal RAG (performance, enterprise security)

Push Multimodal RAG limits by fine-tuning 2026 models with LoRA on custom enterprise datasets, integrate RAGAS for automatic evaluation of faithfulness and cross-modal relevance, secure pipelines against multimodal injections and biases, debug with tools like Weights & Biases, apply optimization techniques like quantization for edge deployment, conduct benchmarks on GPU/TPU hardware, produce quantified performance reports demonstrating ROI for your certifying professional skills.

Module 4Deployment: Scalable Production Multimodal RAG (Docker, Kubernetes, monitoring)

Deploy your 2026 Multimodal RAG systems in Docker containers and orchestrate with Kubernetes for enterprise scalability, integrate FastAPI for low-latency multimodal APIs, configure monitoring with Prometheus and Grafana for retrieval metrics tracking, test under real conditions with simulated load, migrate to cloud like AWS Bedrock or Vertex AI, finalize with a capstone project on business cases like multimodal analysis of marketing videos, receive certification and resources for immediate enterprise autonomy.

Evaluation method

  • Expert MCQ on Multimodal RAG architectures and 2026 tools
  • Evaluation through practical projects and pipeline audits
  • Defense of the deployed live Multimodal RAG system

Learning method

  • Sessions led by AI experts in active production
  • Hands-on exercises on enterprise multimodal datasets
  • Red thread project Multimodal RAG from day 1 to deployment
  • Complete materials, source codes, and unlimited repl.it access

Methods, materials and delivery

The Training Multimodal RAG - Deploying Multimodal AIs 2026 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 - Deploying Multimodal AIs 2026 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 - Deploying Multimodal AIs 2026 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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