Rigorous trainer selection
Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.
- Triple validation: technical, pedagogical, sectoral.
- Minimum rating 4.8/5 over the last 12 sessions.
Training: Mastering PyTorch - Complete Deep Learning for Developers and Data Scientists
Trusted by — schools, companies and industrial groups
41,182 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.
PyTorch training objectives
- Understand in depth the functioning of PyTorch and its main modules
- Know how to prepare, process, and efficiently load data for deep learning projects
- Build and train classic and advanced neural networks (CNN, RNN, GAN...)
- Optimize models and diagnose overfitting/underfitting problems
- Implement complete deep learning workflows on real projects, from prototyping to production
- Leverage GPU and accelerate computations with PyTorch
- Manage serialization, deployment, and industrialization of PyTorch models
- Acquire best practices for coding and documenting collaborative PyTorch projects
Program
PyTorch curriculum: 5 modules over 5 days
Module 1 : Introduction to PyTorch, Tensors & Data Manipulation
Presentation of PyTorch, environment installation, differences with other frameworks. Creation and manipulation of tensors, basic operations, introduction to autograd. Hands-on with Torchvision and dataset management.
Module 2 : Neural Networks with PyTorch: Fundamentals and Customization
Building networks via nn.Module and nn.Sequential. Initialization, forward pass, manual and automatic backward pass. Standard layers (Linear, Convolutional, etc.). Model customization. First supervised training (image classification).
Module 3 : Debugging, Optimization, and Experiment Management
Advanced use of autograd for debugging. Common error handling, visualization of weights/activations. Optimizers (SGD, Adam, RMSProp). Use of callbacks, early stopping, learning rate management.
Module 4 : Advanced Deep Learning: CNN, RNN, GAN, and Transfer Learning
Advanced implementation: convolutional networks for vision, recurrent networks for sequences. GAN basics and use cases. Transfer learning with pre-trained models (ResNet, BERT...). Introduction to PyTorch Lightning for structuring projects.
Module 5 : Production, Deployment, and Best Practices
Model serialization and export. Integration with ONNX. Deployment on server/API, model versioning. GPU optimization, batch processing, distributed computing. Documentation, testing, and team collaboration on real PyTorch projects.
How PyTorch skills are assessed
- Red thread case study (project to complete at the end of each day)
- Intermediate MCQ evaluation
- Final presentation and oral defense of a mini-project
How the PyTorch course is taught
- Interactive courses with numerous concrete examples
- Guided practical workshops and individual exercises
- Collective correction and personalized feedback
- Detailed course materials and skill badges
PyTorch training: access and practical arrangements
The Training: Mastering PyTorch - Complete Deep Learning for Developers and Data Scientists program is delivered onsite or remote (blended-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.
The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.
Equipment required
For the smooth delivery of the Training: Mastering PyTorch - Complete Deep Learning for Developers and Data Scientists program, the following equipment is required:
- Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
- Training environments installed on workstations or accessible online
- Course materials, hands-on exercises and complementary resources
- Post-training access to materials and educational resources
For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.
* contact us for remote delivery feasibility** ratio varies depending on the program
Skills assessment methods
Assessment of skills acquired during the Training: Mastering PyTorch - Complete Deep Learning for Developers and Data Scientists program is performed through:
- During training: case studies, hands-on labs and professional scenarios
- End of training: self-assessment questionnaire and skills evaluation by the trainer
- After training: completion certificate detailing acquired skills
Program accessibility
Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.
Enrollment terms and lead times
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Our method
How Learni guarantees the quality of your PyTorch training
Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.
You meet the trainer beforehand
30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.
- Live briefing on goals and team context.
- Veto right — we swap the trainer for free if needed.
Content tailored to your context
No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.
- Hands-on cases drawn from your stack and projects.
- Program co-written then validated by your team.
Continuous quality follow-up
Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.
- NPS, knowledge quizzes and skills self-assessment.
- Satisfaction guarantee: fully satisfied or free rework.
A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.
Our social commitment
A school kit donated to a child for every training booked
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
FAQ
PyTorch: frequently asked questions
What can participants do after Training: Mastering PyTorch training?+
They can understand in depth the functioning of PyTorch and its main modules, know how to prepare, process, and efficiently load data for deep learning projects and build and train classic and advanced neural networks (CNN, RNN, GAN...). Those are the stated objectives of the Training: Mastering PyTorch program at Intermediate level, checked by the end-of-session assessment.
What does the Training: Mastering PyTorch program cover, day by day?+
Day 1: Introduction to PyTorch, Tensors & Data Manipulation. Day 2: Neural Networks with PyTorch: Fundamentals and Customization. Day 3: Debugging, Optimization, and Experiment Management. Day 4: Advanced Deep Learning: CNN, RNN, GAN, and Transfer Learning. Day 5: Production, Deployment, and Best Practices. The Training: Mastering PyTorch program runs over 5 days, delivered on site.
How is Training: Mastering PyTorch training assessed?+
Assessment relies on red thread case study (project to complete at the end of each day), intermediate MCQ evaluation and final presentation and oral defense of a mini-project. Learni issues a completion certificate together with the individual assessment report at the end of the Training: Mastering PyTorch program, which an L&D team can file as evidence.
How much does Training: Mastering PyTorch training cost per participant?+
Training: Mastering PyTorch training costs $5,775 per participant. For an in-company team, the flat rate starts at $10,395 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does Training: Mastering PyTorch training take?+
5 days, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for Training: Mastering PyTorch training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before Training: Mastering PyTorch training?+
Knowledge of Python and basics of machine learning.
Is a certificate issued after Training: Mastering PyTorch training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
Does Learni provide the equipment for Training: Mastering PyTorch training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
Your professional training, anywhere
Let's build your PyTorch learning path.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
Reply within 24h · Vetted experts · USD invoicing · W-9 available
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