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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: Discovery and Hands-on with ONNX for Interoperability in Artificial Intelligence 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: Discovery and Hands-on with ONNX for Interoperability in Artificial Intelligence 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: Discovery and Hands-on with ONNX for Interoperability in Artificial Intelligence 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 the Open Neural Network Exchange: missions, history, key players. Positioning within the AI ecosystem. Benefits of model interoperability. Overview of supported frameworks and conversion and deployment scenarios. Case study: why and how to choose ONNX?
ONNX environment installation. Introduction to PyTorch, TensorFlow, and Scikit-learn tools for conversion. Practical exercises: exporting a PyTorch model to ONNX, converting a TensorFlow model. Common pitfalls and conversion tips. Visualization of an ONNX model. Management of metadata and export constraints.
Introduction to ONNX Runtime: acceleration, hardware compatibility (CPU, GPU, Edge). Local and cloud deployment (Azure, AWS). Benchmarking of converted models. Setting up a multi-platform inference pipeline. Optimization practices, quantization, and pruning via ONNX. Practical lab: integrating an ONNX model into a REST API and presenting a real-world industrialized case.
Target audience
Developers, data scientists, AI engineers wishing to integrate or deploy multi-platform AI models
Prerequisites
Basic knowledge of artificial intelligence and experience with frameworks such as PyTorch or TensorFlow
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