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 Together AI 2026 - Mastering Collaborative Open-Source AI training are: Basic Python knowledge and elementary machine learning concepts. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Together AI 2026 - Mastering Collaborative Open-Source AI training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Together AI 2026 - Mastering Collaborat... | 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 Together AI 2026 - Mastering Collaborative Open-Source AI 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 Together AI 2026 - Mastering Collaborative Open-Source AI 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 Together AI 2026 - Mastering Collaborative Open-Source AI 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 fundamentals of Together AI 2026 for professional AI projects

Develop skills in deploying certified open-source models

Configure Together AI environments adapted to the enterprise

Implement collaborative training pipelines with Together AI 2026

Optimize AI applications for production in a team

Design scalable and secure AI workflows

Integrate Together AI into modern enterprise stacks

Training program

Module 1Together AI 2026 Fundamentals: installation and first models (CLI, playground, API)

Immersive discovery of the Together AI 2026 platform, quick installation of the environment via CLI and Docker, exploration of the playground to test open-source models like Llama or Mistral, creation of your first inference script, practical exercises on simple enterprise use cases, generation of performance reports to validate skills from the first day.

Module 2Together AI 2026 Models: fine-tuning and customization (Hugging Face tools, datasets)

Deep dive into fine-tuning models with Together AI 2026, preparation of custom datasets via integrated tools, launch of training jobs on cloud GPU, real-time monitoring of metrics via dashboard, practical application on a red thread project like an enterprise chatbot, optimization of hyperparameters for immediate professional results.

Module 3Together AI 2026 Pipelines: automation and CI/CD (workflows, Docker, GitHub Actions)

Building end-to-end pipelines with Together AI 2026, Docker integration to containerize models, setting up CI/CD via GitHub Actions and Together endpoints, automated tests on real enterprise scenarios, deployment of a secure predictive API, collaborative exercises to simulate DevOps teams, deliverable: functional pipeline ready for production.

Module 4Together AI 2026 Scalability: optimization and monitoring (serving, observability, costs)

Mastery of optimization to scale with Together AI 2026, configuration of multi-GPU serving for high loads, implementation of monitoring with Prometheus and Grafana, cloud cost reduction up to 50% via advanced techniques, practical cases on e-commerce traffic spikes, log analysis for rapid debugging, production of a custom dashboard for your enterprise.

Module 5Together AI 2026 Projects: enterprise integration and deployment (secure APIs, security)

Synthesis via a complete red thread project with Together AI 2026, integration into a full-stack like FastAPI and Streamlit, securing endpoints with OAuth and rate-limiting, tests in real enterprise conditions, code review by the expert trainer, preparation for production deployment on Together cloud, delivery of a certifying portfolio to boost your CV.