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.
1 seat held for the next session
30:00Held for another
Request a call back and an advisor reaches you within 24 business hours, Monday to Saturday.
Trusted by — schools, companies and industrial groups
Every program built with a dedicated engineer
Learning 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
Our social commitment
A school kit donated to a child for every training
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
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.
Don't let this gap widen
Why this program matters
Without intermediate PyTorch mastery, 70% of data scientists struggle to scale their models, resulting in productivity losses estimated at 25% according to Gartner.
Companies risk AI deployment delays, with 40% of ML projects failing in production for lack of optimization, costing up to 500k€ per failed initiative (Forrester).
Your career stagnates against growing demand: 85% of ML job postings require advanced PyTorch.
Invest in this certification training to avoid obsolescence, secure promotions and company ROI starting today.
Program
Module 1PyTorch 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 2PyTorch 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 3PyTorch 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 4PyTorch 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.
Evaluation method
- 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
Learning method
- 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
Methods, materials and delivery
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.
Our method
Training quality, guaranteed at every step
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.
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FAQ
Frequently asked questions
How much does the Training PyTorch - Mastering Advanced Deep Learning Models training cost?+
The price is $4,620 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training PyTorch - Mastering Advanced Deep Learning Models training?+
The training lasts 4 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Mastery of Python, basics in machine learning, use of NumPy and Pandas, notions of neural networks
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote
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