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Training RAG Pipeline 2026 - Deploy Advanced Generative AI Pipelines

Ref: ZZS568
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
distanciel

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Learning objectives

  • Master the design of 2026 RAG pipelines to boost enterprise AI performance
  • Develop certified professional skills in advanced ETL for RAG data ingestion
  • Design and optimize Spark streams for real-time vector processing
  • Implement scalable Kafka-Airflow orchestrations for robust RAG pipelines
  • Deploy resilient 2026 RAG architectures ready for industrial production
  • Evaluate and secure RAG pipelines for GDPR compliance and high availability
  • Acquire certified expertise to advance your Data Engineering career

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 1RAG Pipeline 2026 Fundamentals: Advanced Architecture and Vectorization (LLMs, Embeddings)

Dive into innovative 2026 RAG architectures through concrete cases from leading companies, configure advanced embeddings with Hugging Face and FAISS, perform practical exercises on hybrid retrieval, integrate LLMs like GPT-4o or Llama 3 for augmented generation, produce a first functional pipeline prototype tested in real conditions, analyze precision metrics to iterate quickly.

Module 2ETL for RAG Pipeline 2026: Data Ingestion and Preprocessing (Spark, Pandas)

Build robust ETL for 2026 RAG pipelines using Apache Spark to scale massive data cleaning, implement ingestion pipelines from SQL/NoSQL databases and APIs, apply advanced vectorial transformations with intelligent chunking, test on 1TB real datasets, generate deliverables like optimized Spark scripts, measure impact on retrieval latency for 40% efficiency gains.

Module 3Spark Processing in RAG Pipeline 2026: Scaling and Optimization (MLlib, Delta Lake)

Optimize the Spark core of your 2026 RAG pipelines with MLlib for vectorial feature engineering, deploy Delta Lake for ACID storage of embeddings, simulate clustered workloads on Databricks, integrate distributed joins for hybrid search, perform comparative benchmarks, produce performant Spark DAGs reducing cloud costs by 30%, apply advanced tuning for high concurrency.

Module 4Kafka-Airflow Orchestration for RAG Pipeline 2026: Real-Time Streams (Streams, DAGs)

Orchestrate fluid 2026 RAG pipelines via Kafka Streams for real-time ingestion, configure complex Airflow DAGs with custom Spark-Kafka operators, manage retries and monitoring with Prometheus, test fault-tolerant scenarios on Kubernetes clusters, deploy end-to-end live pipelines, analyze logs for expert debugging, deliver reusable templates boosting data engineering productivity by 50%.

Module 5Deployment and Tuning of RAG Pipeline 2026: Production-Ready and Monitoring (Kubernetes, Grafana)

Finalize your 2026 RAG pipelines in production on Kubernetes with dedicated Helm charts, implement A/B testing and canary releases for LLMs, integrate Grafana for advanced RAG metrics dashboards, secure with OAuth and vector store encryption, complete a full capstone project on a real client case, evaluate ROI via cost/performance simulations, obtain immediately deployable blueprints for your company.

Evaluation method

  • Daily technical quizzes on RAG concepts and Spark-Kafka tools
  • Final project: end-to-end deployment of a 2026 RAG pipeline evaluated by experts
  • Qualiopi certification validating expert Data Engineering skills

Learning method

  • 70% hands-on: Real labs on simulated Spark and Kafka clusters
  • 30% theory: Feedback from industrial 2026 RAG projects
  • Individual coaching to customize pipelines to your company's challenges
  • Fortune 500 case studies for concrete and inspiring benchmarks

Methods, materials and delivery

The Training RAG Pipeline 2026 - Deploy Advanced Generative AI Pipelines 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 RAG Pipeline 2026 - Deploy Advanced Generative AI Pipelines 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 RAG Pipeline 2026 - Deploy Advanced Generative AI Pipelines 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
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« 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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