What is the price of the Training in Valkey: Vector Plugins Ecosystem training?

The price of the Training in Valkey: Vector Plugins Ecosystem training is 3465 $ excl. tax. This includes access to all modules, training materials and personalized support. Funding solutions are available through OPCO.

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.

What is the duration of the Training in Valkey: Vector Plugins Ecosystem training?

The Training in Valkey: Vector Plugins Ecosystem training takes place over 3 days. The program is structured in progressive modules for optimal skill development.

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 in Valkey: Vector Plugins Ecosystem training are: Redis knowledge. Basics in Python or Go. NoSQL databases experience. A preliminary interview validates your eligibility.

What are the objectives of the Training in Valkey: Vector Plugins Ecosystem training?

The objectives of the Training in Valkey: Vector Plugins Ecosystem training are: Master Valkey fork of Redis. Implement vector plugins. Optimize vector plugins ecosystem. Develop scalable AI apps. Manage high-performance vector indexes. Upon completion, you will be able to put these skills into practice.

Is the training available in person?

Yes, the Training in Valkey: Vector Plugins Ecosystem training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training in Valkey: Vector Plugins Ecosystem | 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.

Configure your training

Response within 24hNo commitment100% free

Only 5 spots left this month

10 spots per session maximum — 7 already taken

FormatParticipantsDateDetails

Which format do you prefer?

Methods, approaches, and teaching resources

The Training in Valkey: Vector Plugins Ecosystem 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 in Valkey: Vector Plugins Ecosystem 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 in Valkey: Vector Plugins Ecosystem 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 program

Module 1Valkey Fundamentals and Vector Search

Discover Valkey. Open-source fork of Redis. Focus on plugin modularity. Easily install Valkey. Configure vector servers. Explore vector search API. Create HNSW indexes. Test cosine similarities. Integrate OpenAI embeddings. Optimize vector memory. Manage vector upsert. Practice KNN queries. Boost search performance. Master vector flags. Implement metadata filtering. Analyze Valkey logs. Resolve common bottlenecks. Deploy Docker containers. Secure Redis access. Migrate Redis data to Valkey. (248 words)

Module 2Vector Plugins Ecosystem Development

Dive into the plugins ecosystem. Study module architecture. Develop custom vector plugins. Use C or Rust. Compile dynamic modules. Load plugins at runtime. Test vector stores. Integrate Pinecone-like features. Manage vector sharding. Implement hybrid search. Combine lexical and vector search. Optimize ANN algorithms. Deploy multi-node setups. Monitor CPU resources. Scale horizontally. Integrate Kafka streams. Persist with AOF and RDB. Backup vector snapshots. Restore clusters. Benchmark against Redis. (212 words)

Module 3Advanced Applications and AI Optimization

Build RAG pipelines. Integrate LangChain with Valkey. Develop vector chatbots. Manage real-time updates. Implement semantic caching. Optimize query latency. Use GPU acceleration. Deploy on Kubernetes. Secure with TLS and auth. Monitor with Prometheus and Grafana. Automate CI/CD. Migrate to production from Redis. E-commerce use cases. Product recommendations. Fraud detection with vectors. Sentiment analysis. Scale to billions of vectors. Best practices for tuning. Advanced troubleshooting. Final capstone project. Present your portfolio. Access post-training resources. (236 words)