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 Weaviate - Mastering Vector Databases for AI training are: Basic knowledge of Python programming, introductory concepts in AI and vector embeddings, installed development environment.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Weaviate - Mastering Vector Databases for AI training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training Weaviate - Mastering Vector Databases… | 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 Weaviate - Mastering Vector Databases for 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 Weaviate - Mastering Vector Databases for 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 Weaviate - Mastering Vector Databases for 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 access terms and deadlines

Training objectives

Master the installation and configuration of Weaviate in certified professional training.

Develop skills in creating vector schemas for enterprise applications.

Implement data indexing and querying with Weaviate for semantic searches.

Integrate Weaviate with external AI tools in a professional context.

Design real-world use cases optimizing vector performance.

Acquire sustainable skills in vector databases for scalable AI projects.

Training program

Module 1Weaviate Fundamentals: Installation, Schemas, and Initial Indexing (Docker, Python Client, Practical Exercises)

Dive into Weaviate with a guided installation via Docker in just a few minutes, configure your first vector class schemas adapted to textual and multimodal data, import real datasets using the official Python client, perform hands-on exercises on batch indexing of thousands of objects, test HNSW modules for fast search, receive configuration templates as immediate deliverables, alternating concise theory and intensive practice over 7 hours to anchor your professional skills from the first day.

Module 2Weaviate Querying and Integrations: Advanced Searches and Use Cases (GraphQL, Hybrid Modules, Concrete Projects)

Get into action with GraphQL queries to extract similar vectors in milliseconds, explore hybrid modules combining keywords and semantics for ultra-precise results, integrate Weaviate with LangChain and OpenAI via live examples, develop a complete RAG project on company documents, optimize performance with sharding and replication, analyze real metrics on recall and latency, produce a functional prototype as final deliverable, consolidating your skills in certified training over 7 interactive remote hours.