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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.
10 spots per session maximum — 8 already taken
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Without mastery of industrial TensorFlow deployment for AI models, 85% of enterprise projects fail to reach production, wasting 6-12 months and $2-5 million in sunk development costs per initiative.
Suboptimal scaling and monitoring trigger 70% of AI outages, incurring $100,000+ per hour in downtime and revenue loss.
Unprepared teams expose companies to regulatory fines and eroded market share, stalling innovation pipelines.
Every quarter without expertise escalates these vulnerabilities into existential threats.
The Training TensorFlow Enterprise: Mastering the Industrial Deployment of Your AI Models 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 TensorFlow Enterprise: Mastering the Industrial Deployment of Your AI Models 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 TensorFlow Enterprise: Mastering the Industrial Deployment of Your AI Models 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.
Presentation of TensorFlow Enterprise: overview, differences with the open-source version, GCP support. Structuring an industrial AI project: best practices, model lifecycle, setting up reproducible environments. Demonstration: preparation of a Google Cloud environment adapted to TensorFlow workflows.
Performance optimization (TPUs, GPUs, multi-node distribution), managed infrastructures (AI Platform, Vertex AI). Securing AI models: access management, traffic regulation, reliability monitoring, backups/restorations. Workshop: Deploying a TensorFlow model in production with advanced monitoring.
MLOps pipeline with TensorFlow Extended (TFX): ingestion, training, validation, automated deployment. Use of Docker, Kubernetes, and CI/CD for service continuity. Production on GCP with versioning and rollback. Hands-on: Integrate and monitor a complete TFX pipeline.
Scalability management, fault tolerance, high availability. GDPR compliance, auditability, logs, and advanced monitoring. Protection of APIs, models, and sensitive data. Practical workshop: Securing and auditing a deployed model.
Implementation of A/B testing, shadow deployment, post-production monitoring, version management. Analysis of usage metrics, continuous adjustments, drift anticipation. Prepare maintenance, long-term support, documentation, Google Cloud support management. Complete case study: Deployment of a successful AI project with full lifecycle management.
8 participants max.
$6,353 / per person
5 days
remoteTarget audience
Data engineers, data scientists, cloud architects, ML engineers wishing to industrialize their models with TensorFlow in an enterprise context
Prerequisites
Mastery of Python, basic knowledge of deep learning and cloud environment (GCP or equivalent)
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Intermediate
€2,310.002 days
remote8 pers. max.Intermediate€3,465.003 daysremote8 pers. max.Intermediate€3,465.003 daysremote8 pers. max.Intermediate€2,310.002 daysremote8 pers. max.
