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 Vercel AI SDK - Integrating Generative AI in Production training are: Mastery of Next.js 14+, advanced TypeScript, and AI model APIs like OpenAI. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Vercel AI SDK - Integrating Generative AI in Production training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Vercel AI SDK - Integrating Generative ... | 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 Vercel AI SDK - Integrating 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 Vercel AI SDK - Integrating 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 Vercel AI SDK - Integrating 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 Vercel AI SDK to develop professional and scalable AI applications

Implement text generation flows and real-time streaming

Design autonomous AI agents with tool calling and advanced RAG

Optimize AI performance in enterprise Next.js environments

Deploy and monitor certified AI solutions on Vercel

Develop AI integration skills for certified projects

Training program

Module 1Vercel AI SDK Setup: Advanced Configuration and Providers (Next.js, TypeScript, OpenAI)

Quick installation of Vercel AI SDK in an existing Next.js 14 project, configuration of providers like OpenAI and Anthropic for professional AI flows, exploration of hooks useChat and useCompletion with practical exercises on real enterprise cases, creation of a first interactive AI component, unit tests and live debugging, production of a functional deliverable ready for integration.

Module 2Vercel AI SDK Streaming Generation: Dynamic Text and Completions (Advanced Hooks, AI UI/UX)

Implementation of real-time streams with Vercel AI SDK for smooth and engaging AI responses, customization of hooks to handle user interruptions and network errors, exercises on enterprise chatbots with persistent conversation history, integration of Markdown rendering for rich content, performance optimization with suspense and smooth transitions, delivery of a complete and responsive chat interface.

Module 3Vercel AI SDK Tool Calling: Intelligent Agents and External Functions (APIs, Databases)

Development of AI agents via Vercel AI SDK with tool calling to execute custom functions like API queries or complex calculations, connection to external services such as Pinecone vector databases, practical workshops on business scenarios like customer automation, management of reasoning loops and fallback strategies, creation of a scalable multi-tool agent, documentation and end-to-end tests for professional deployment.

Module 4Advanced RAG with Vercel AI SDK: Retrieval and Enriched Context (Embeddings, Vector Stores)

Implementation of Retrieval-Augmented Generation with Vercel AI SDK for contextualized and precise AI responses, generation of embeddings with Hugging Face models, indexing in stores like Vercel Postgres or Supabase, exercises on enterprise cases with internal documents, prompt chaining for result refinement, optimization of costs and latency, production of a RAG module integrated into a Next.js app with performance metrics.

Module 5Vercel AI SDK Deployment: Scaling, Monitoring, and Security (Vercel Edge, Observability)

Serverless deployment of AI applications on Vercel with Vercel AI SDK, configuration of Edge Functions for minimal global latency, setup of monitoring with Vercel Analytics and Sentry for AI error traceability, workshops on prompt security and rate limiting, GPU cost optimization via intelligent caching, finalization of the red thread project with GitHub Actions CI/CD, delivery of certifiable source code and enterprise maintenance plan.