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 BullMQ 2026 - Mastering Scalable AI Task Queues training are: JavaScript/Node.js basics, Redis fundamentals, installed development environment. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training BullMQ 2026 - Mastering Scalable AI Task Queues training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training BullMQ 2026 - Mastering Scalable AI Tas... | 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 BullMQ 2026 - Mastering Scalable AI Task Queues 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 BullMQ 2026 - Mastering Scalable AI Task Queues 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 BullMQ 2026 - Mastering Scalable AI Task Queues 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 installation of BullMQ 2026 in a professional certifying training course

Develop producers and consumers for scalable AI tasks

Configure priorities and retries with enterprise-ready skills

Implement distributed jobs to optimize AI performance

Design BullMQ monitoring dashboards for professional supervision

Optimize asynchronous workflows by integrating BullMQ into modern AI stacks

Training program

Module 1BullMQ 2026 Fundamentals: installation, basic queues (Node.js, Redis, first AI jobs)

Discover the quick installation of BullMQ 2026 with Redis locally and in the cloud, configure your first queues for AI tasks such as batch inference, produce simple jobs via Node.js with practical exercises on producer scripts, test reactive consumers in real-time, analyze initial logs for debugging, and generate your first completion reports, all while integrating real business cases for immediate skill ramp-up.

Module 2Advanced BullMQ 2026: priorities, retries, distributed jobs (business rules, AI scaling)

Dive into advanced priority management and automated retries for critical AI jobs, implement limited concurrency patterns with BullMQ 2026, develop distributed flows on Redis clusters to scale massive inferences, practice failure scenarios with automatic reconnection, integrate custom hooks for Slack or email notifications, and validate through exercises on real AI datasets, ensuring robust professional skills.

Module 3Production BullMQ 2026: monitoring, optimization, deployments (dashboards, AI perf)

Master Bullboard dashboards for real-time monitoring of BullMQ 2026 queues, optimize performance with rate limiting and backpressure for intensive AI pipelines, deploy in production with Docker/Kubernetes and secrets management, test high availability on multi-node setups, analyze Prometheus/Grafana metrics for fine-tuning, and finalize with a capstone project: a complete AI orchestrator, ready for certifying enterprise use.