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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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The Training Neo4j - Optimizing Graphs for Enterprise 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.
To ensure the quality of the Training Neo4j - Optimizing Graphs for Enterprise AI training, Learni provides the following 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.
The assessment of skills acquired during the Training Neo4j - Optimizing Graphs for Enterprise AI training is carried out through:
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.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Dive into expert Cypher queries for matching complex patterns on massive graphs, configure composite and full-text indexes to accelerate searches, apply built-in algorithms like shortestPath and PageRank on real enterprise datasets, perform practical exercises on fraud detection cases, produce performant reports with APOC and Bloom visualization.
Optimize your Neo4j databases for extreme workloads by analyzing execution plans with EXPLAIN/PROFILE, tune JVM and heap configurations to minimize latency, implement causal clustering sharding with Java/Python drivers, test scalability on simulations with 1M+ nodes, develop monitoring scripts with Neo4j Ops Manager, measure concrete gains on your red thread project.
Integrate Neo4j into ML pipelines via the GDS library for graph-centric algorithms like Louvain and Node2Vec, generate vector embeddings for semantic similarity, connect to TensorFlow/PyTorch for advanced predictions, apply real-world cases in recommendation systems and anomaly detection, export results in Kafka/Spark-compatible formats, validate models on real enterprise data.
Secure Neo4j deployments with fine-grained RBAC roles and LDAP/OIDC authentication, implement at-rest and in-transit encryption, configure incremental backups and disaster recovery, integrate auditing with Sentry plugins, test Cypher injection and DoS attacks, migrate to Neo4j Aura for hybrid cloud, document GDPR-compliant policies for certification audits.
Deploy Neo4j clusters on Kubernetes using Helm charts for high availability, integrate Fabric for multi-graph federation, monitor with Prometheus/Grafana and custom alerts, automate CI/CD pipelines with GitHub Actions, optimize AWS/GCP cloud costs, finalize red thread project with interactive dashboard, prepare for expert Neo4j certification.
Target audience
Data engineers, data architects, BI analysts seeking advanced graph skills
Prerequisites
Advanced SQL proficiency, NoSQL experience, intermediate Cypher
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