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 PyTorch - Mastering Advanced Deep Learning Models
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
- Master advanced tensors and autograd in PyTorch for efficient computations in professional training
- Develop CNNs and RNNs with PyTorch, acquiring certifiable skills for the enterprise
- Implement optimized training pipelines, integrating DataLoader and professional optimizers
- Design scalable deep learning models ready for MLOps deployment
- Optimize PyTorch model performance using advanced techniques and debugging
- Deploy AI applications in production, enhancing enterprise machine learning skills
Program
PyTorch curriculum: 4 modules over 4 days
Module 1 : PyTorch Fundamentals: Advanced Tensors, Autograd, and First Modules (Exercises on Real Datasets)
Discover multidimensional tensors and vectorized operations in PyTorch, practicing autograd for automatic gradient computation on concrete examples like linear regression. Build your first custom nn.Module modules, test them with standard loss functions, and debug using TensorBoard. Apply these fundamentals to a simplified MNIST dataset, producing a trained and visualized model, with individualized trainer feedback to consolidate your professional deep learning skills.
Module 2 : PyTorch Vision: CNNs, Transfer Learning, and Data Augmentation (Models on Medical Images)
Dive into convolutional networks with Conv2D and pooling layers in PyTorch, implementing ResNet via torchvision for rapid transfer learning. Augment datasets with transforms and albumentations, train on CIFAR-10 or custom medical images, monitoring overfitting with early stopping. Produce precise metrics like accuracy and F1-score, export optimized weights, and discuss enterprise use cases, strengthening your mastery of PyTorch tools for computer vision in a professional context.
Module 3 : PyTorch Sequential: RNNs, LSTMs, Basic Transformers (NLP and Time Series)
Explore RNNs and LSTMs for sequential processing, coding predictive models on IMDb texts or financial time series with PyTorch. Integrate embeddings and introductory attention mechanisms, optimize with AdamW and LR schedulers, manage vanishing gradients with guided exercises. Evaluate using BLEU score or MSE, generate batch predictions, and integrate TorchText for advanced preprocessing, delivering a complete pipeline ready for enterprise AI applications.
Module 4 : PyTorch Production: Optimization, MLOps Deployment, and TorchServe (API and Monitoring)
Optimize PyTorch models with TorchScript, quantization, and ONNX export for fast inference on CPU/GPU. Deploy via TorchServe or Docker, configure RESTful endpoints with Prometheus monitoring, and integrate basic CI/CD for MLOps. Test on real cases like anomaly detection, measure latency and throughput, produce a performance report with dashboards. Conclude with a personal capstone project, including coaching for enterprise adaptation, certifying your scalable deployment skills.
How PyTorch skills are assessed
- Interactive quizzes and daily practical exercises to validate learning outcomes
- Final project on a real business case with PyTorch and expert feedback
- Qualiopi-certified attestation evaluating intermediate deep learning skills
How the PyTorch course is taught
- Hands-on projects on professional datasets for immediate application
- Guided practical exercises led by certified PyTorch trainers
- Case studies from leading AI and machine learning companies
- Post-training support with e-learning resources and dedicated Q&A
PyTorch training: access and practical arrangements
The Training PyTorch - Mastering Advanced Deep Learning Models 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 PyTorch - Mastering Advanced Deep Learning Models 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 PyTorch - Mastering Advanced Deep Learning Models 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
Which tools are used in PyTorch training?+
Hands-on work runs on exercises on Real Datasets, models on Medical Images, NLP, time Series, API and monitoring. Those tools come from the PyTorch program itself, delivered on site over 4 days, so participants practise on the stack they will use at work.
What can participants do after PyTorch training?+
They can master advanced tensors and autograd in PyTorch for efficient computations in professional training, develop CNNs and RNNs with PyTorch, acquiring certifiable skills for the enterprise and implement optimized training pipelines, integrating DataLoader and professional optimizers. Those are the stated objectives of the PyTorch program at Intermediate level, checked by the end-of-session assessment.
What does the PyTorch program cover, day by day?+
Day 1: PyTorch Fundamentals: Advanced Tensors, Autograd, and First Modules (Exercises on Real Datasets). Day 2: PyTorch Vision: CNNs, Transfer Learning, and Data Augmentation (Models on Medical Images). Day 3: PyTorch Sequential: RNNs, LSTMs, Basic Transformers (NLP and Time Series). Day 4: PyTorch Production: Optimization, MLOps Deployment, and TorchServe (API and Monitoring). The PyTorch program runs over 4 days, delivered on site.
How is PyTorch training assessed?+
Assessment relies on interactive quizzes and daily practical exercises to validate learning outcomes, final project on a real business case with PyTorch and expert feedback and qualiopi-certified attestation evaluating intermediate deep learning skills. Learni issues a completion certificate together with the individual assessment report at the end of the PyTorch program, which an L&D team can file as evidence.
How much does PyTorch training cost per participant?+
PyTorch training costs $4,620 per participant. For an in-company team, the flat rate starts at $7,865 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 PyTorch training take?+
4 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 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 PyTorch training?+
Mastery of Python, basics in machine learning, use of NumPy and Pandas, notions of neural networks.
Is a certificate issued after 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 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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