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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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Allan Busi
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Allan BusiNov 1, 20268 min readSheffieldThe Training Qwen 2026 - Deploying High-Performance LLMs in the Enterprise 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 Qwen 2026 - Deploying High-Performance LLMs in the Enterprise 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 Qwen 2026 - Deploying High-Performance LLMs in the Enterprise 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.
Dive into the internal layers of Qwen 2026 through PyTorch code dissections, set up fine-tuning environments with LoRA to adapt the model to your enterprise data, perform practical exercises on sectoral datasets, generate your first optimized outputs, and produce an initial performance analysis report with precise metrics such as perplexity and inference speed.
Learn to prepare and load professional datasets into Qwen 2026, apply PEFT techniques for efficient fine-tuning without massive GPU overhead, test various hyperparameters in interactive sessions, develop a customized model for cases like code generation or semantic analysis, validate results via automated benchmarks, and integrate everything into a reproducible pipeline for your projects.
Set up inference servers with vLLM to boost Qwen 2026 speed up to 10x, containerize via Docker and orchestrate with Kubernetes for enterprise scalability, implement secure REST APIs to integrate Qwen 2026 into your apps, simulate high loads in practical exercises, set up monitoring with Prometheus and Grafana, and deploy a live prototype ready for production.
Integrate RAG to enrich Qwen 2026 with your internal knowledge bases, develop multi-task agents via LangChain by solving concrete business cases, strengthen security against jailbreaks with Guardrails and adversarial tests, optimize latency and costs via quantization and distillation, finalize a complete ongoing project, and prepare a certifying rollout plan for your team.
10 participants max.
$5,390 / per person
28 heures
remoteTarget audience
Data scientists, AI engineers, ML developers seeking to upskill on advanced LLMs
Prerequisites
Mastery of Python, PyTorch or TensorFlow, experience in fine-tuning LLM models
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