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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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Master competitive analysis skills essential for product teams with this step-by-step guide, including tools, frameworks, and 2026 trends like AI-driven insights.
Allan Busi
Apr 9, 202612 min read
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Allan BusiMay 1, 20268 min readCardiffThe Training Multimodal RAG 2026 - Mastering Multimodal Generative AI 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 Multimodal RAG 2026 - Mastering Multimodal Generative AI 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 Multimodal RAG 2026 - Mastering Multimodal Generative AI 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.
Discovery of the principles of multimodal Retrieval-Augmented Generation, installation of a development environment with LangChain and Hugging Face, creation of embeddings for text and images via CLIP, first exercises on mixed datasets, construction of a simple multimodal Q&A prototype, analysis of real business cases to identify precision gains.
Setting up vector databases like FAISS and Pinecone for multimodal data, integration of LLMs like LLaVA for image-text processing, development of hybrid RAG pipelines with reranking, practical exercises on various business documents, augmented generation tests, prompt optimization to reduce hallucinations, production of a testable functional deliverable.
Realization of a red thread project on a real business case integrating audio and video, containerized deployment with Docker and Streamlit, performance evaluation via RAGAS metrics, optimization exercises for 2026 scalability, group code review, enterprise integration plan, provision of resources for autonomous continuation.
10 participants max.
$2,888 / per person
21 hours
in-personTarget audience
Data scientists, AI developers, data project managers wishing to upskill in multimodal RAG
Prerequisites
Python basics, notions of AI and language models (LLM)
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€1,050.007 hours
in-person10 pers. max.expert€4,200.0028 heuresin-person10 pers. max.intermediate€1,050.007 heuresremote10 pers. max.Beginner€2,200.002 daysremote8 pers. max.