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Training LanceDB - Optimizing AI Vector Searches

Ref: VGU437
10 people max.
6125€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

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Learning objectives

  • Master the LanceDB architecture for scalable enterprise vector databases
  • Develop high-performance indexing pipelines with the LanceDB SDK
  • Implement hybrid and filtered vector queries for AI
  • Design certified RAG applications integrating LanceDB
  • Optimize LanceDB performance for production deployments
  • Integrate LanceDB with professional AI frameworks like LangChain

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1LanceDB Architecture: Advanced Configuration and Data Ingestion (Python SDK, Schemas, Batching)

Dive into installing a scalable LanceDB cluster, configure complex vector schemas adapted to your enterprise datasets, ingest millions of embeddings via the Python SDK with optimized batching, test persistence on disk and cloud, perform practical exercises on real multimodal data cases, produce your first functional vector index with performance metrics.

Module 2LanceDB Indexing: Advanced Techniques and Optimization (HNSW, IVF, Metadata)

Explore HNSW and IVF indexing algorithms for ultra-fast searches, integrate rich metadata for semantic filtering, optimize hyperparameters on massive datasets using LanceDB tools, develop real-time upsert and deletion scripts, apply these methods to an enterprise red thread project, measure speed and accuracy gains with concrete benchmarks.

Module 3LanceDB Queries: Hybrid Similarity Search and Full-Text (ANN, KNN, Reranking)

Master ANN and KNN queries for precise vector similarities, combine with full-text search for advanced hybridization, implement custom reranking on cosine or Euclidean scores, test on AI use cases like product recommendation, develop complex filtered queries by metadata, analyze results via LanceDB dashboards, optimize for sub-second latency in production.

Module 4LanceDB Integration: RAG and AI Frameworks (LangChain, LlamaIndex, HuggingFace Embeddings)

Integrate LanceDB into complete RAG pipelines with LangChain and LlamaIndex, generate dynamic embeddings via HuggingFace Transformers, build reactive AI agents on vector databases, manage secure multi-user sessions, deploy end-to-end prototypes on sensitive enterprise data, evaluate generated response fidelity, produce an operational RAG deliverable ready for certification.

Module 5Scaling LanceDB: Production Deployment and Monitoring (Kubernetes, Observability, Security)

Deploy LanceDB in distributed mode on Kubernetes with horizontal sharding, configure monitoring via Prometheus and Grafana for real-time metrics, secure access with API keys and RBAC, optimize cloud costs on AWS or GCP, simulate extreme loads with stress-test tools, finalize your red thread project with expert code review, prepare roadmap for certified enterprise integration.

Evaluation method

  • Technical MCQ on LanceDB and vector search at the end of the training
  • Evaluation through practical exercises and pipeline optimization
  • Defense of the RAG red thread project with expert trainer

Learning method

  • Courses by certified LanceDB trainer in professional practice
  • Hands-on exercises on real enterprise datasets and open-source tools
  • Progressive RAG red thread project over 5 days
  • Complete pedagogical support and unlimited online resources

Methods, materials and delivery

The Training LanceDB - Optimizing AI Vector Searches program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training LanceDB - Optimizing AI Vector Searches program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training LanceDB - Optimizing AI Vector Searches program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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