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 Replicate - Deploying Generative AI in Production training are: Basic knowledge of Python or JavaScript programming and REST API usage. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Replicate - Deploying Generative AI in Production training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Replicate - Deploying Generative AI in… | 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 Replicate - Deploying Generative AI in Production 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 Replicate - Deploying Generative AI in Production 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 Replicate - Deploying Generative AI in Production 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 Replicate for professional AI applications

Develop AI predictions with ready-to-use models

Configure scalable Replicate workflows for enterprise environments

Implement Replicate integration into certified projects

Optimize costs and performance of AI models via Replicate

Acquire professional skills in serverless AI deployment

Training program

Module 1Replicate Fundamentals: Installation and First Models (API, Playground, Authentication)

Discovery of the Replicate platform via the interactive playground, creation of a professional account and generation of a secure API key, exploration of popular AI models like Stable Diffusion or Llama, first prediction tests via command line with curl, practical exercises on image and text generation, production of a simple deliverable to integrate into a personal project, with immediate trainer feedback to validate learning.

Module 2Replicate Integration: Developing Client Applications (Python/JS SDK, Webhooks)

Installation of official Replicate SDKs in Python and JavaScript, coding client applications to launch asynchronous predictions, webhook management to notify AI results, implementation of basic user interfaces with Streamlit or React, real business cases such as AI chatbots or personalized image generation, collaborative pair exercises, finalization of a functional prototype deployed locally with complete documentation.

Module 3Replicate Scalability: Optimization and Advanced Workflows (Versioning, Fine-Tuning)

Configuration of model versions for stable production deployments, parameter optimization to reduce latency and GPU costs, creation of multi-model chained workflows via Replicate API, exploration of lightweight fine-tuning on enterprise datasets, simulated load tests with tools like Artillery, resolution of common real-world AI failure cases, production of an automated pipeline ready for DevOps integration, with performance metrics analysis.

Module 4Replicate Deployment: Production and Monitoring (Vercel, Security, Costs)

Deployment of Replicate applications on Vercel or Heroku with integrated CI/CD, securing API keys and managing enterprise quotas, monitoring predictions via Replicate dashboards and third-party tools like Datadog, budget optimization with real cost-per-prediction calculations, incident simulation and advanced debugging, finalization of the end-to-end project with a professional portfolio, issuance of certificates and post-training action plan for immediate team adoption.