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PyTorch Initiation Training - Create Your First Deep Learning Models

Ref: YGW559
10 people max.
4200 € HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
4 journées
distanciel

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Learning objectives

  • Install and configure PyTorch with CUDA
  • Manipulate tensors and autograd
  • Build simple neural networks
  • Train models on real datasets
  • Evaluate and optimize performance
  • Deploy a basic PyTorch model

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this PyTorch training, 70% of deep learning projects fail at the basics, wasting 6 months of R&D and 50k€ in useless salaries.

  • Poorly managed tensors cause recurrent crashes, underperforming models (accuracy <70%) block product launches, and lack of CUDA multiplies training times by 10.

  • Falling behind on PyTorch exposes you to competition: trained companies see +30% AI ROI in 3 months.

  • Risk of personal frustration, non-competitive CV against certified data scientists.

  • Invest 28h to avoid these concrete losses and turn AI into a strategic advantage.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1PyTorch Installation and Tensors: CUDA Tools, Basic Exercises (Vector Manipulations)

Discover PyTorch by installing the complete environment with CUDA to accelerate your computations, manipulate your first tensors through interactive exercises on simple datasets, create automatic operations with autograd, test real transformations like image normalization, and produce your first tensor graphs to visualize data flows, while solving concrete cases that prepare you for practical AI.

Module 2Linear Networks: nn Modules, Regression (Iris Dataset, Training Loops)

Dive into PyTorch nn modules to build linear models, train regression on the Iris dataset with SGD optimization loops, calculate MSE losses live, adjust hyperparameters through guided exercises, visualize learning curves, and generate reliable predictions on unseen data, to master training from day one and boost your confidence in deep learning.

Module 3Basic CNNs: Image Classification (MNIST, Convolutions, DataLoader)

Build your first CNNs with PyTorch on MNIST, use DataLoader to load image batches, implement convolutions and pooling through practical exercises, train with CrossEntropyLoss, optimize with Adam, test accuracy on validation, and deploy a functional image classifier, while analyzing common errors for optimal results that motivate you to tackle complex projects.

Module 4Advanced Projects and Deployment: TorchScript, ONNX (Complete AI Model)

Complete an end-to-end final project on custom classification, export to TorchScript and ONNX for deployment, optimize with pruning and quantization, measure GPU/CPU performance, debug via TensorBoard, and produce a deliverable ready to integrate into an app, with personalized feedback to solidify your skills and launch you immediately into production AI.

Evaluation method

  • Daily practical exercises, graded final project, validation quiz

Learning method

  • 70% hands-on practice on real cases, 30% interactive theory, collaborative exercises

Methods, materials and delivery

The PyTorch Initiation Training - Create Your First Deep Learning Models program is delivered onsite or remote (blended-learning, e-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 PyTorch Initiation Training - Create Your First 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 PyTorch Initiation Training - Create Your First 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

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
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.

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.

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