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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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30 free minutes with a training advisor — no commitment.
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Don't let this gap widen
Without advanced MLflow mastery, 70% of ML projects fail in production according to Gartner, wasting 50k€/project in engineer time and rework.
Non-reproducible models cause 40% more frequent errors, x3 deployment delays, revenue losses up to 20% from faulty AI.
Avoid data/ops silos, critical downtime, missed audits: train for 5x ML ROI in 6 months, secure scaling and GDPR compliance.
The Training MLflow Advanced - Deploy ML Models in Production 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 MLflow Advanced - Deploy ML Models in Production 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 MLflow Advanced - Deploy ML Models in Production 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.
Install and configure MLflow Tracking Server with robust backend, practice automatic logging of metrics/hyperparameters via PyTorch/TensorFlow exercises, explore interactive UI to compare runs, generate custom reports on real optimization cases, integrate Git artifacts, everything to scale your ML experiments in a dynamic team.
Master Model Registry for secure versioning, deploy models via MLflow Serving on Kubernetes, simulate CI/CD pipelines with GitHub Actions, test A/B testing and drift monitoring, solve concrete production cases like GPU scaling, deliverables: enterprise-ready deployable scripts, boost your ML workflows independently.
Target audience
Data Scientists, ML Engineers, AI DevOps professionals seeking to upskill in MLOps.
Prerequisites
Proficiency in Python, ML frameworks (TensorFlow/PyTorch), beginner MLflow, Docker, Kubernetes basics.
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