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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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Professional Training training in Dallas in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Explore the future of asynchronous communication training for distributed teams. Discover strategies, tools, and trends shaping effective collaboration across time zones by May 2026.
Professional Training training in Memphis in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Artificial Intelligence training in San Francisco in October 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
The Training MCP (Model Context Protocol) - Optimizing AI Model Contexts in Production 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 MCP (Model Context Protocol) - Optimizing AI Model Contexts in Production 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 MCP (Model Context Protocol) - Optimizing AI Model Contexts in Production 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 deep into the Model Context Protocol architecture, install expert environments with Hugging Face Transformers and LangChain, configure custom tokenizers for long contexts, perform exercises on secure contextual injection, produce a first functional MCP pipeline tested in real enterprise conditions, analyze initial performance metrics to identify immediate gains.
Develop advanced MCP state managers using Redis and vector stores like Pinecone, integrate lossless semantic contextual compression mechanisms, simulate real-time multi-user scenarios, build a reusable module for professional AI applications, test robustness against contextual overflows, generate optimized latency reports demonstrating 50% production gains.
Master MCP profiling with TensorBoard and PyTorch Profiler, apply contextual sharding techniques on GPU clusters, optimize for distributed inferences using Ray and Kubernetes, conduct before/after comparative benchmarks, develop automated tuning scripts, produce a customized monitoring dashboard for DevOps teams, highlight business impacts through concrete enterprise cases.
Integrate MCP with secure APIs using Kong and OAuth2, implement homomorphic encryption for sensitive contexts, manage contextual leaks via automated audits, simulate injection attacks and mitigate them live, deploy CI/CD pipelines for certified MCP, collaborate on hybrid cloud/on-prem capstone project, document GDPR compliance for immediate professional deployments.
Deploy MCP applications in production with Docker Swarm and AWS EKS, configure observability via Prometheus/Grafana for contextual metrics, launch A/B tests on massive loads, analyze logs for rapid iterations, finalize capstone project with expert code review, prepare scalable enterprise rollout, receive personalized toolkit for post-training autonomy.
Target audience
AI Engineers, ML Developers, Software Architects expert in contextual protocols for advanced skill development
Prerequisites
Advanced mastery of LLMs, expert Python, REST/GraphQL API protocols, context management in AI inference
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