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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning objectives
- Master Agentic RAG to create professional autonomous AI agents
- Develop certified multi-agent architectures for enterprise
- Implement intelligent workflows with LangChain and LlamaIndex tools
- Optimize response accuracy via dynamic adaptive retrieval
- Design scalable Agentic RAG systems for 2026 production
- Evaluate and deploy secure AI agents in business contexts
Our social commitment
A school kit donated to a child for every training
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Don't let this gap widen
Why this program matters
Without mastering Agentic RAG, 68% of AI projects fail due to hallucinations and imprecise retrieval, costing an average of 200k€ per incident in reworked development time.
Companies lose 45% productivity on non-augmented data analysis, with 3x more critical errors.
In 2026, 82% of recruiters reject profiles without autonomous agent skills, risking competitive lag against competitors delivering AI 5x faster.
Every quarter without training widens the fatal business gap.
Program
Module 1Agentic RAG Fundamentals: Concepts and Environment (LangChain, vector stores)
Dive into Agentic RAG principles to boost LLMs with decision-making agents, install the environment via Poetry and Docker, configure embeddings with HuggingFace and Pinecone, perform your first augmented retrievals, test simple agents on real enterprise cases like intelligent Q&A, produce a functional prototype with initial accuracy metrics.
Module 2Agentic RAG Architecture: Multi-Agent Tools and Reasoning (LlamaIndex, CrewAI)
Design hybrid Agentic RAG architectures for complex tasks, integrate LlamaIndex for advanced indexing and CrewAI for multi-agent orchestration, develop custom routing and fallback tools, apply to large business datasets, generate autonomous workflows that decide retrieval or generation actions, validate with practical exercises and deliverable diagrams.
Module 3Agentic RAG Implementation: Advanced Workflows and Tools (ReAct, hierarchical planning)
Implement Agentic RAG agents with ReAct patterns and multi-step planning, code dynamic tool-calling to external APIs and vector databases, optimize prompts for chain-of-thought reasoning, handle concrete cases like enterprise document analysis or semantic search, debug live with LangSmith observability, deliver a fully functional tested agent.
Module 4Agentic RAG Optimization: Evaluation and Tuning (RAGAS, adaptive fine-tuning)
Evaluate Agentic RAG performance via RAGAS frameworks and custom benchmarks, measure faithfulness and answer relevance on your projects, apply hybrid reranking and intelligent query rewriting, fine-tune retrievers with LoRA on enterprise data, reduce hallucinations by 50% in practice, produce optimization reports and production-ready automated pipelines.
Module 5Agentic RAG Deployment 2026: Scalability and Security (FastAPI, Kubernetes, monitoring)
Deploy Agentic RAG systems to production via FastAPI and Docker Compose, scale with Kubernetes and Ray Serve for massive loads, integrate RAG security with guards and rate-limiting, monitor in real-time via Prometheus and Grafana, test end-to-end on critical business scenarios, finalize your red thread project with cloud deployment and skills certificate.
Evaluation method
- Multiple-choice quiz to validate learning outcomes at the end of the training
- Continuous evaluation through practical Agentic RAG exercises
- Defense of the multi-agent red thread project in front of the trainer
Learning method
- Courses led by an active AI expert trainer
- Practical exercises on real enterprise Agentic RAG cases
- Progressive red thread project throughout the training
- Complete course materials provided to each participant
Methods, materials and delivery
The Training Agentic RAG - Developing Autonomous AI Agents program is delivered onsite or remote (blended-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 Agentic RAG - Developing Autonomous AI Agents 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 Agentic RAG - Developing Autonomous AI Agents 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
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.
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.
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.
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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FAQ
Frequently asked questions
How much does the Training Agentic RAG - Developing Autonomous AI Agents training cost?+
The price is $5,775 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training Agentic RAG - Developing Autonomous AI Agents training?+
The training lasts 5 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Python proficiency, LLM basics, basic RAG and vector database APIs
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote
This training across cities
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