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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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The Training GraphRAG 2026 - Boosting LLMs with Intelligent Graphs training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training GraphRAG 2026 - Boosting LLMs with Intelligent Graphs training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training GraphRAG 2026 - Boosting LLMs with Intelligent Graphs training is carried out through:
Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Immersive introduction to the key concepts of GraphRAG 2026, quick setup of the Python environment with dedicated libraries like NetworkX and LangChain, automated data extraction to build your first knowledge graphs from business documents, practical exercises on real complex Q&A cases, interactive visualization of entities and relationships with Neo4j, creation of your personal graph as a concrete deliverable to consolidate immediately applicable learnings.
Implementation of complete GraphRAG 2026 pipelines connected to LLMs like GPT or Llama, formulation of advanced queries leveraging graphs for precise responses without hallucinations, comparative tests of RAG vs GraphRAG on business datasets, performance optimization with indexing and pruning, quantitative evaluation using RAGAS metrics, simplified cloud deployment with Docker, completion of a professional red thread project deliverable and ready to integrate into your data workflows for immediate productivity gains.
Target audience
Data scientists, AI developers, ML engineers seeking to upskill in advanced RAG
Prerequisites
Python basics, LLM fundamentals, and initial exposure to RAG
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