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.
Learning objectives
- Manipulate multidimensional tensors and autograd for efficient calculations.
- Build and train CNNs on real image datasets.
- Implement RNN and LSTM architectures for time series.
- Optimize models with DataLoader, GPU, and augmentation techniques.
- Evaluate performance using advanced metrics and visualizations.
- Deploy PyTorch models in production with TorchServe.
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, your DL models take 40% longer to train, leading to critical project delays and explosive cloud costs up to 5k€/month.
65% of data scientists fail deployments due to autograd bugs or poorly optimized GPUs, losing business opportunities like real-time fraud detection.
Risk obsolescence against Torch-savvy competitors, or invest 21h to boost ML ROI x3, deploy confidently, and dominate your AI challenges next week.
Program
Module 1Advanced Tensors and Autograd: PyTorch Tools for Deep Learning (tensors, gradients, first models).
Dive into PyTorch tensors with complex vectorized manipulations, activate autograd for automatic differentiation on custom functions, build a fully connected network on MNIST with practical exercises, visualize gradients using TensorBoard, generate reusable code deliverables, and benefit from expert feedback to accelerate your mastery.
Module 2Convolutional and Recurrent Networks: CNN/RNN Methods (ResNet, LSTM, CIFAR datasets).
Design modern CNNs like ResNet on CIFAR-10 through interactive workshops, train RNN/LSTM for time series prediction on financial datasets, apply dropout and batch normalization for regularization, test on real image and text cases, produce optimized saved models, and experience the power of PyTorch that turns your ideas into stunning results.
Module 3Optimization and Deployment: GPU Performance, TorchServe (DataLoader, ONNX, inference).
Accelerate training with DataLoader and CUDA on dedicated GPUs, optimize hyperparameters via practical grid search, export to ONNX for interoperability, deploy inference APIs with TorchServe on real e-commerce cases, debug common errors in groups, and conclude with a certified final project deliverable, ready to integrate PyTorch into production tomorrow.
Evaluation method
- Daily interactive quizzes on key concepts.
- Practical projects evaluated by the trainer.
- Final project with personalized feedback and certification.
Learning method
- Hands-on projects on real datasets.
- Pair programming exercises.
- Ready-to-use Jupyter notebooks.
Methods, materials and delivery
The Training PyTorch - Master High-Performance DL 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 - Master High-Performance DL 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 - Master High-Performance DL 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 - Master High-Performance DL Models training cost?+
The individual price is $3,465 (USD). A detailed quote is sent within one business day.
How long is the Training PyTorch - Master High-Performance DL Models training?+
The training lasts 3 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, advanced knowledge of NumPy and Pandas, basics in deep learning with TensorFlow or beginner PyTorch.
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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