Training PyTorch - Master High-Performance DL Models

$3,465

  • 3 days
  • Onsite
  • 10 people max.
Ref: NEX249
10 people max.
$3,465
In-company rate: from $6,290 for the whole team
On-site and certification exam on quote
3 days
Onsite

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.

Allan BUSI, Learni trainer · AI expert
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction
Flag of the United StatesBuilt for US teams
Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone

Trusted by — schools, companies and industrial groups

41,181 programs · 25 countries

  • Aptar
  • ArcelorMittal
  • Equans
  • EDF
  • Ubisoft
  • Microsoft
  • Atos

Every program built with a dedicated engineer

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Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.

PyTorch training 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.

Program

PyTorch curriculum: 3 modules over 3 days

Module 1 : Advanced 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 2 : Convolutional 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 3 : Optimization 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.

How PyTorch skills are assessed

  • Daily interactive quizzes on key concepts.
  • Practical projects evaluated by the trainer.
  • Final project with personalized feedback and certification.

How the PyTorch course is taught

  • Hands-on projects on real datasets.
  • Pair programming exercises.
  • Ready-to-use Jupyter notebooks.

PyTorch training: access and practical arrangements

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.

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.

Step 1

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.
Step 2

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.
Step 3

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.
Step 4

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.

A child walking to school with a backpack
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
Enroll and offer a kit
FAQ

PyTorch: frequently asked questions

Which tools are used in PyTorch training?+
Hands-on work runs on tensors, gradients, first models, resNet, LSTM and CIFAR datasets. Those tools come from the PyTorch program itself, delivered on site over 3 days, so participants practise on the stack they will use at work.
What can participants do after PyTorch training?+
They can manipulate multidimensional tensors and autograd for efficient calculations, build and train CNNs on real image datasets and implement RNN and LSTM architectures for time series. 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: Advanced Tensors and Autograd: PyTorch Tools for Deep Learning (tensors, gradients, first models). Day 2: Convolutional and Recurrent Networks: CNN/RNN Methods (ResNet, LSTM, CIFAR datasets). Day 3: Optimization and Deployment: GPU Performance, TorchServe (DataLoader, ONNX, inference). The PyTorch program runs over 3 days, delivered on site.
How is PyTorch training assessed?+
Assessment relies on daily interactive quizzes on key concepts, practical projects evaluated by the trainer and final project with personalized feedback and certification. 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 $3,465 per participant. For an in-company team, the flat rate starts at $6,290 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?+
3 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, advanced knowledge of NumPy and Pandas, basics in deep learning with TensorFlow or beginner PyTorch.
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.
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