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 the fundamentals of PyTorch to build deep learning models in a professional context
- Develop practical skills in creating and training neural networks tailored to business needs
- Design efficient data pipelines using PyTorch tools for certification projects
- Implement robust machine learning solutions with TensorFlow and PyTorch in an MLOps environment
- Optimize model performance while integrating best practices for enterprise deployment
- Configure complete training environments to promote continuous team learning
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
Companies that fail to master PyTorch lose competitiveness to rivals who deploy high-performance AI models quickly.
Recent studies show that 65 % of machine learning projects fail due to weak internal expertise, resulting in costly delays and lost market share.
Professionals without certified PyTorch training watch their careers stall as demand surges in tech sectors.
Failing to invest in these skills now creates a gap that becomes hard to close amid rapid MLOps tool changes.
Program
Module 1Theme: Introduction to PyTorch and building neural networks (tools, methods, deliverables)
Participants discover the basics of PyTorch through practical exercises in creating tensors and dynamic graphs. They explore nn.Module modules to define simple architectures, build a first classification model on a real dataset, manipulate optimizers and loss functions, and produce a complete deliverable with visualization of learning curves to validate the training outcomes.
Module 2Theme: Advanced training and MLOps integration with PyTorch (tools, methods, deliverables)
The second day focuses on model optimization, the use of DataLoader for processing large volumes of data, the integration of TensorBoard for metrics tracking, and an introduction to MLOps practices with model saving and versioning. Learners deploy a complete pipeline on a concrete business case and submit a production-ready deliverable including scripts and technical documentation.
Evaluation method
- Knowledge validation quizzes after each module
- Final practical project evaluated by the trainer
- Self-assessment of acquired skills at the end of the training
Learning method
- Practical exercises on personal laptop
- Real-world use cases from the professional world
- Detailed course materials provided in digital format
- Access to a private Git repository for completed projects
Methods, materials and delivery
The Training PyTorch - Developing High-Performance AI 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 - Developing High-Performance AI 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 - Developing High-Performance AI 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 - Developing High-Performance AI Models training cost?+
The price is $2,940 (USD) per participant. A detailed quote is sent within one business day.
How long is the Training PyTorch - Developing High-Performance AI Models training?+
The training lasts 2 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?+
Basic knowledge of Python, object-oriented programming concepts, and familiarity with simple mathematical concepts such as matrices
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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