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 ComfyUI - Master Professional AI Workflows in 4 Days training are: Mastery of Stable Diffusion, basic Python knowledge, regular use of ComfyUI in basic mode.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training ComfyUI - Master Professional AI Workflows in 4 Days training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training ComfyUI - Master Professional AI Workfl... | 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 ComfyUI - Master Professional AI Workflows in 4 Days 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 ComfyUI - Master Professional AI Workflows in 4 Days 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 ComfyUI - Master Professional AI Workflows in 4 Days 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 program

Module 1Day 1: Advanced Architectures: Multi-Node Workflows (ComfyUI Manager, chaining, optimized deliverables)

Dive into custom ComfyUI nodes, configure multi-step chains with LoRA and embeddings, perform exercises on real text-to-image generation cases, test rapid iterations for pro renders, master basic debugging via logs and dynamic previews, produce your first exportable workflow.

Module 2Day 2: Custom Nodes and Scripting: Python Extensions (dev tools, API integration, automated scripts)

Create custom Python nodes in ComfyUI, integrate extensions via Manager and Git, develop scripts for batch image processing, apply to concrete projects like video upscaling, optimize with GPU tuning, generate reusable modular deliverables, boost creativity with hybrid flows.

Module 3Day 3: Optimization and Scaling: Performance Tuning (VRAM management, batching, profiling tools)

Analyze bottlenecks in ComfyUI, implement massive batching and low-memory VRAM modes, test on professional datasets to accelerate renders x5, integrate advanced ControlNet for precise poses, profile with built-in tools, produce scalable workflows for production, turn limitations into competitive advantages.

Module 4Day 4: Professional Deployment: API, Servers (Docker, cloud integration, monitoring deliverables)

Deploy ComfyUI as API via FastAPI and Docker, configure AWS/GCP cloud servers, automate error monitoring and updates, simulate real client cases in team, generate performance dashboards, finalize certified projects with certification, leave with a ready-to-use deployment kit.