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 - Deploying Open-Source AI Models training are: Python basics and machine learning fundamentals. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Together AI - Deploying Open-Source AI Models training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Together AI - Deploying Open-Source 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 Together AI - Deploying Open-Source AI Models 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 - Deploying Open-Source AI Models 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 - Deploying Open-Source AI Models 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 Together AI for professional AI projects

Develop certifying skills in deploying open-source models

Configure enterprise-adapted Together AI environments

Implement fine-tuning workflows for business applications

Optimize AI models with Together AI in a professional context

Design scalable and secure AI pipelines for the enterprise

Training program

Module 1Together AI Fundamentals: Installation and First Models (CLI, Playground)

Immersive discovery of the Together AI platform through quick installation of the development environment, exploration of the interactive playground to test open-source models like Llama or Mistral, creation of your first Python script calling the Together AI API, practical exercises on simple business cases, generation of textual content and analysis of responses to evaluate performance, production of an initial test report with basic prompt optimization.

Module 2Together AI API: Integration and Professional Workflows (Python SDK, Endpoints)

Hands-on dive into the Together AI API with use of the official Python SDK, configuration of asynchronous calls for massive requests, seamless integration into an existing web project using Flask or FastAPI, exercises on error handling and tokens, development of a basic chatbot connected to Together AI, real-world enterprise testing with cost and performance monitoring, delivery of a deploy-ready functional prototype.

Module 3Together AI Fine-Tuning: Model Personalization (Datasets, Hyperparameters)

Hands-on learning of fine-tuning on Together AI by uploading your company datasets, selection and configuration of optimal hyperparameters for Llama-3 or Mixtral, launching supervised training jobs with real-time monitoring via dashboard, evaluation of fine-tuned models using precise metrics like perplexity and BLEU, exercises on concrete text classification or assisted generation cases, creation of a custom exportable model, complete documentation for production reuse.

Module 4Together AI Deployment: Scalability and Security in the Enterprise (Inference API, Monitoring)

Mastery of advanced deployment with Together AI's Inference API for scalable servers, securing endpoints via authentication and rate limiting, integration with Kubernetes for hybrid cloud environments, continuous monitoring of performance and costs using built-in tools, practical exercises on an ongoing business project with A/B model testing, final optimization for minimal latency, delivery of a certified production deployment plan with post-training support.