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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: Mastering PyTorch - From Beginner to Creating 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: Mastering PyTorch - From Beginner to Creating 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: Mastering PyTorch - From Beginner to Creating 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 PyTorch and the machine learning ecosystem, installation, first exploration in a notebook, hands-on with tensors, basic operations (addition, multiplication, slicing), memory management and CUDA device (GPU/CPU).
Creating and loading datasets, DataLoader, data visualization, manual implementation of linear regression and simple classification, loss and gradient, first supervised trainings, introduction to optimization with torch.optim.
Creating models with nn.Module, setting up an MLP (multilayer perceptron) for real tasks, weight initialization, callbacks, early stopping and training monitoring, advanced optimization techniques (momentum, Adam), introduction to regularization (Dropout, L2/L1), saving, loading and exporting models, quick deployment of a simple model.
Target audience
Developers, data scientists, engineers, students, and professionals eager to get started with PyTorch for Deep Learning
Prerequisites
Basic proficiency in Python, notions of applied mathematics (matrices, functions, derivatives)
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