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 - Orchestrating Multi-Agent AI Agents training are: Basic knowledge of Python and familiarity with AI or text generation. A preliminary interview validates your eligibility.

Is the training available in person?

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

Training CrewAI - Orchestrating Multi-Agent AI… | 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 - Orchestrating 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.

Teaching resources provided

To ensure the quality of the Training CrewAI - Orchestrating Multi-Agent 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 - Orchestrating Multi-Agent 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 access terms and deadlines

Training objectives

Master the fundamentals of CrewAI to develop professional multi-agent systems

Develop autonomous and collaborative AI agents tailored for business use

Configure custom tasks and tools in certified CrewAI

Implement intelligent crews for complex workflows

Optimize multi-agent orchestration with LLMs in production

Integrate CrewAI into existing professional environments

Deploy scalable and maintainable CrewAI solutions

Training program

Module 1CrewAI Fundamentals: Installation and First AI Agents (Python, LLM, Practical Exercises)

Quick installation of CrewAI via pip in a dedicated Python environment, configuration of LLM models like OpenAI or Grok for intelligent responses, creation of your first agent capable of executing simple tasks like data analysis or web research, practical exercises on real professional cases, interactive debugging with the trainer, production of a functional testable agent that already demonstrates collaborative power, immediately valuing your modern AI skills.

Module 2CrewAI Tasks and Tools: Collaborative Workflows (Custom Tools, API, Enterprise Integrations)

Definition of structured tasks in CrewAI for automated processes, development of custom tools via Python such as web scrapers or API connectors, setup of multi-agent crews that communicate and delegate intelligently, practical workshops on business scenarios like marketing automation or report generation, iterative testing to refine performance, creation of a complete deliverable workflow ready to integrate into your professional projects, boosting your productivity by the end of the day.

Module 3Advanced CrewAI Crews: Orchestration and Deployment (Docker, Monitoring, Certifying Projects)

Complete orchestration of complex crews with agent hierarchy and robust error management, advanced integration of memory and external tools for scalable applications, containerization via Docker for easy production deployment, performance monitoring with logs and key metrics, completion of a red thread project on a real business case like a multi-task virtual assistant, personalized code review by the trainer, finalization of a certifying portfolio demonstrating your new collaborative AI skills ready for use.