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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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Cybersecurity training in Sheffield in November 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Professional Training training in Dallas in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Artificial Intelligence training in Mesa in September 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
Professional Training training in Fort Worth in July 2026 with Learni. Certified, expert trainers, eligible for employer funding. Free quote.
The Training AutoGen 2026 - Orchestrating Advanced Multi-Agent AI Agents 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 AutoGen 2026 - Orchestrating Advanced Multi-Agent AI Agents 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 AutoGen 2026 - Orchestrating Advanced Multi-Agent AI Agents 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 modular architecture of AutoGen 2026, install the environment with pip and conda for secure enterprise setups, configure user-proxy and assistant agents with local models like Llama3 or cloud GPT-4o, complete practical exercises on initial agent dialogues, test automatic debugging scenarios, produce a first functional multi-agent workflow with detailed logging, immediately leverage your skills in collaborative AI.
Explore GroupChatManager to orchestrate debates between specialized agents, implement advanced state management with vector memory and HNSW for rich contextual interactions, develop concrete cases like automated R&D brainstorming or collaborative data analysis, integrate custom callbacks for intelligent routing, optimize turn-taking with dynamic priorities, build and deploy a multi-agent prototype solving a real business problem, measure efficiency via built-in metrics.
Create custom Python tools for AutoGen agents, integrate third-party APIs like OpenAI Tools or vector databases such as Pinecone for advanced RAG, configure tool-enabled agents for complex tasks like automated web scraping or mathematical optimization, test on enterprise projects with robust error handling, develop a hybrid agent combining code execution and semantic search, evaluate performance with AutoGen benchmarks, produce reusable deliverables boosting your professional AI productivity.
Deploy AutoGen 2026 pipelines in Docker containers for scalability, orchestrate with Kubernetes and Ray for massive workloads, implement monitoring with Prometheus and distributed tracing, optimize LLM costs via caching and intelligent batching, simulate cloud deployments on AWS or Azure with CI/CD GitHub Actions, finalize a certifiable red thread project solving a business challenge, receive expert feedback and post-training action plan for immediate enterprise integration.
Target audience
AI Engineers, data scientists, ML developers seeking to upskill in autonomous agents for enterprise
Prerequisites
Advanced mastery of Python, LLMs like GPT-4, multi-agent frameworks such as LangChain or CrewAI
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