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Training Multimodal RAG 2026 - Mastering Advanced Generative AI

Ref: LOT589
10 people max.
5500€ 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
in-person

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Learning objectives

  • Master Multimodal RAG 2026 architectures to develop certified professional skills in backend AI
  • Implement multimodal augmented retrieval pipelines tailored to business needs
  • Design scalable REST APIs integrating Node.js and microservices for AI applications
  • Optimize RAG 2026 performance with multimodal text-image-audio embeddings
  • Deploy RAG solutions in production via resilient and secure microservices
  • Develop concrete business use cases for actionable certified training
  • Integrate advanced open-source tools for rapid upskilling in generative AI

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 of Multimodal RAG 2026: Architectures and Embeddings (Node.js, Vector Databases)

Discover the key principles of Multimodal RAG 2026 through dedicated Node.js modules, install tools like Pinecone and Hugging Face Transformers to generate multimodal embeddings, complete practical exercises on indexing text and image data, build your first simple retrieval pipeline, analyze real business cases to validate data flows, and produce a functional testable deliverable by the end of the day, strengthening your professional backend AI skills.

Module 2Advanced Retrieval in Multimodal RAG 2026: Hybridization and Ranking (REST APIs, Initial Microservices)

Dive into hybrid retrieval techniques for Multimodal RAG 2026, configure REST APIs with Express.js to expose multimodal search endpoints, integrate rankers like Cohere Rerank, practice on real datasets mixing images and text, develop a prototype microservice dedicated to reranking, simulate enterprise loads to test scalability, and generate performance reports as deliverables, optimizing your certified backend development skills.

Module 3Augmented Generation in Multimodal RAG 2026: LLMs and Fusion (Node.js Streaming, Advanced Tools)

Explore generative augmentation in Multimodal RAG 2026 by connecting retrieval to multimodal LLMs like Llama 3 or GPT-4V via Node.js, implement response streaming for smooth UX, fuse multimodal contexts with dynamic prompts, complete hands-on workshops on e-commerce and customer support scenarios, deploy a complete API service, measure output fidelity with RAGAS metrics, and finalize a production-ready microservices prototype, boosting your professional expertise.

Module 4Microservices Architecture for Multimodal RAG 2026: Scalability and Observability (Docker, Kubernetes Basics)

Build a microservices architecture for Multimodal RAG 2026 by containerizing your Node.js services with Docker, orchestrate with introductory Kubernetes for horizontal scaling, integrate Prometheus and Grafana for observability, test resilience with light chaos engineering on multimodal flows, develop secure RESTful API gateways, apply to a complete enterprise use case like a multimodal virtual assistant, and produce dashboards and deployments as concrete deliverables, consolidating your advanced backend skills.

Module 5Production Deployment of Multimodal RAG 2026: Security, Monitoring, and Optimization (CI/CD, Best Practices)

Master production deployment of Multimodal RAG 2026 with GitHub Actions CI/CD pipelines, secure REST APIs via JWT and rate limiting in Node.js, optimize cloud costs with quantized embeddings, monitor real-time multimodal RAG performance, implement A/B tests on live microservices, review real enterprise architectures for final iterations, and generate a certified portfolio with source code, documentation, and functional demo, validating your complete professional training.

Evaluation method

  • Daily interactive quizzes on Multimodal RAG 2026 concepts
  • Practical projects evaluated by backend AI experts
  • Final certifying exam with real business case

Learning method

  • Active pedagogy with 70% hands-on practice on Node.js and microservices
  • Real business use cases for realistic immersion
  • 3-month post-training support included for skills consolidation
  • Qualiopi certification validating intermediate Multimodal RAG expertise

Methods, materials and delivery

The Training Multimodal RAG 2026 - Mastering Advanced Generative AI 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 Generative AI 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 Generative AI 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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