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-Task AI Agents training are: Advanced mastery of Python, experience in generative AI, use of LLM APIs like OpenAI, development of scalable applications.. A preliminary interview validates your eligibility.

Is the training available in person?

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

Training CrewAI - Orchestrating Multi-Task 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-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 - 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 - 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 access terms and deadlines

Training objectives

Master the CrewAI architecture to design multi-agent workflows in enterprise settings.

Develop specialized agents with professional certifying skills.

Design collaborative tasks and tools optimized for advanced AI.

Implement scalable crews integrating prompt engineering and deep learning.

Deploy CrewAI solutions in production to boost productivity.

Optimize agent interactions for complex enterprise projects.

Training program

Module 1CrewAI Fundamentals: Agent Architecture and Tasks (Python, LangChain, LLM APIs)

Discover the installation and configuration of CrewAI using Python and LangChain, set up your first agents with precise roles and integrated tools, implement sequential and parallel tasks on real-world business automation cases, test basic interactions in real-time with practical exercises on real datasets, produce a functional crew prototype with exportable deliverables for immediate validation.

Module 2Advanced CrewAI: Tools, Processes, and Multi-Agent Orchestration (Prompt Engineering, Custom Tools)

Dive into creating custom tools and optimizing prompts for intelligent agents, orchestrate complex processes with hierarchies and dynamic delegations, integrate deep learning for advanced contextual decisions, simulate enterprise scenarios like collaborative data analysis or automated report generation, develop and debug multi-agent crews through interactive workshops, generate performance metrics to evaluate efficiency.

Module 3CrewAI Deployment: Scalability, Monitoring, and Real-World Cases (Docker, Cloud, Security)

Master deploying crews in production with Docker and cloud services like AWS or Azure, configure advanced monitoring and logging for real-time supervision, integrate security and error handling in critical environments, apply CrewAI to professional case studies in AI marketing or automated customer support, optimize for scale with quantified benchmarks, finalize a capstone project with certification of acquired skills.