Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Training CrewAI 2026 - Orchestrating Multi-Task AI Agents training are: Advanced proficiency in Python, experience with LLMs like GPT-4, familiarity with LangChain and autonomous agents. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training CrewAI 2026 - Orchestrating Multi-Task AI Agents training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training CrewAI 2026 - Orchestrating Multi-Task… | Learni

The story of Learni

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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Methods, approaches, and teaching resources

The Training CrewAI 2026 - Orchestrating Multi-Task 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.

Teaching resources provided

To ensure the quality of the Training CrewAI 2026 - Orchestrating Multi-Task AI Agents training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and 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.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Training CrewAI 2026 - Orchestrating Multi-Task AI Agents training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

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.

Training objectives

Master the multi-agent architecture of CrewAI 2026 for complex professional workflows

Develop intelligent crews optimized for business with Deep Learning integration

Design advanced prompts via Prompt Engineering for collaborative agents

Implement hierarchical tasks and dynamic delegations in certified training

Optimize AI agent performance with monitoring and scaling tools

Deploy CrewAI 2026 solutions in production to boost professional skills

Training program

Module 1CrewAI 2026 Fundamentals: Multi-Agent Architecture and Advanced Configuration (Python, LangChain, LLM Tools)

Discover the evolution of CrewAI 2026 through practical exercises on creating hierarchical crews, configure specialized agents with precise roles and integrated tools like LangChain, test collaborative interactions on real business cases, generate deliverables like workflow diagrams and optimized scripts, integrate Deep Learning for intelligent decisions, while mastering task hierarchies for smooth and scalable automations.

Module 2Advanced CrewAI 2026 Applications: Deployment and Optimization (Prompt Engineering, Monitoring, Production Scaling)

Dive into Prompt Engineering to refine the behaviors of multi-task agents, deploy complete crews on cloud environments with real-time monitoring using tools like Prometheus, optimize performance through LLM model tuning and advanced error handling, complete a final collaborative project simulating a real business scenario, produce evaluation reports and scaling plans, consolidate your skills for certified implementations in professional artificial intelligence.