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
- Master the fundamentals of ONNX Runtime for model inference in enterprise settings
- Develop certifiable skills in cross-platform AI model execution
- Configure ONNX Runtime inference sessions on professional CPU and GPU
- Implement basic optimizations for production performance
- Integrate ONNX Runtime into Python applications for real-world projects
- Design scalable inference pipelines in professional training
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 this upskilling, your team accumulates a technological gap that translates directly into productivity loss.
Organizations that don't train their talents on key topics see their competitiveness drop.
Every quarter without training is a gap widening with competitors who invest.
The cost of inaction quickly exceeds that of well-targeted training.
Program
Module 1ONNX Runtime Fundamentals: Installation and First Inferences (Python, ONNX Models, Sessions)
Complete discovery of the ONNX Runtime environment via quick installation with pip and conda, creation of inference sessions on simple models like MNIST or ResNet, exploration of Python APIs to load and execute ONNX graphs, practical exercises on converting TensorFlow/PyTorch to ONNX, first runs with prediction visualization, production of an initial performance report to evaluate enterprise gains.
Module 2ONNX Runtime Inference: Advanced Execution on CPU/GPU (Bindings, Providers, Batching)
Deep dive into CPU and CUDA providers to accelerate ONNX Runtime inference, session configuration with input/output tensor management, practice of dynamic batching to handle multiple simultaneous requests, tests on real datasets like COCO for image classification, manual graph optimization via integrated tools, realization of a comparative benchmark demonstrating 3x speedup, immediate application to a concrete business case in certifiable training.
Module 3ONNX Runtime Deployment: Production Integration and Monitoring (Docker, APIs, Optimization)
Building a REST API with FastAPI integrating ONNX Runtime for scalable inference, containerization via Docker for cloud-ready deployment, setting up monitoring with Prometheus for latency traceability, exercises on quantized optimization for edge devices, simulation of an end-to-end enterprise pipeline, finalization of a deployable capstone project with complete documentation, highlighting acquired skills for professional CV.
Evaluation method
- Multiple-choice quiz to validate acquired knowledge at the end of the ONNX Runtime training
- Continuous evaluation through practical inference exercises
- Presentation of the capstone deployment project to the expert trainer
Learning method
- Courses led by an active ONNX Runtime expert trainer
- Practical exercises on real ML business cases and public datasets
- Progressive capstone project to master production inference
- Complete course materials and code examples provided to each participant
Methods, materials and delivery
The Training ONNX Runtime - Deploy Optimized 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 ONNX Runtime - Deploy Optimized 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 ONNX Runtime - Deploy Optimized 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 ONNX Runtime - Deploy Optimized AI Models training cost?+
The individual price is $3,465 (USD). A detailed quote is sent within one business day.
How long is the Training ONNX Runtime - Deploy Optimized AI 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?+
Python basics, machine learning fundamentals, and standard model formats
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.
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