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.
Training ONNX Runtime - Deploy Optimized AI Models
Trusted by — schools, companies and industrial groups
25,809 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.
ONNX Runtime training objectives
- Master the fundamentals of ONNX Runtime to deploy professional AI models
- Develop skills in converting and executing ONNX models in an enterprise environment
- Implement optimized inference with ONNX Runtime across various environments
- Configure integration pipelines for certified AI applications
- Optimize inference performance for scalable professional projects
- Design cross-platform deployments with ONNX Runtime in production
ONNX Runtime curriculum: 3 modules over 3 days
Module 1 : Fundamentals: Install ONNX Runtime and run first models (Python, conversion tools)
Quick installation of ONNX Runtime in a dedicated Python environment, conversion of TensorFlow or PyTorch models to ONNX format using official tools, execution of simple inferences on real datasets, practical exercises to load and predict with your own models, analysis of outputs to validate results, creation of a first professional script ready for enterprise use, with guided debugging by the trainer.
Module 2 : Optimization: Accelerate ONNX Runtime inference (CPU/GPU providers, quantization)
Exploration of ONNX Runtime execution providers for CPU and NVIDIA GPU, application of quantization techniques to reduce model size without loss of precision, optimization of computation graphs via operator fusion, comparative performance tests on concrete business cases, integration into performant Python scripts, production of personal benchmarks, iterative adjustments for measurable gains up to 5x faster.
Module 3 : Deployment: Integrate ONNX Runtime in production (API, containers, monitoring)
Development of a REST API with Flask to serve ONNX Runtime models, containerization via Docker for scalable deployments, configuration of real-time inference performance monitoring, exercises on AWS or Azure cloud integration, practical business cases with simulated traffic, finalization of a deployable ongoing project, delivery of optimized source code and certified production deployment plan.
How ONNX Runtime skills are assessed
- Multiple-choice quiz to validate learning outcomes at the end of the training
- Continuous assessment through practical exercises
- Presentation of the ongoing project to the trainer
How the ONNX Runtime course is taught
- Instructor-led sessions by an active expert trainer
- Hands-on exercises based on real business cases
- Progressive ongoing project throughout the training
- Comprehensive course materials provided to each participant
ONNX Runtime training: access and practical arrangements
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.
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 ONNX Runtime 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.
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.
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
FAQ
ONNX Runtime: frequently asked questions
Which tools are used in ONNX Runtime training?+
Hands-on work runs on python, conversion tools, CPU, GPU providers, quantization and API. Those tools come from the ONNX Runtime program itself, delivered on site over 3 days, so participants practise on the stack they will use at work.
What can participants do after ONNX Runtime training?+
They can master the fundamentals of ONNX Runtime to deploy professional AI models, develop skills in converting and executing ONNX models in an enterprise environment and implement optimized inference with ONNX Runtime across various environments. Those are the stated objectives of the ONNX Runtime program at Beginner level, checked by the end-of-session assessment.
What does the ONNX Runtime program cover, day by day?+
Day 1: Fundamentals: Install ONNX Runtime and run first models (Python, conversion tools). Day 2: Optimization: Accelerate ONNX Runtime inference (CPU/GPU providers, quantization). Day 3: Deployment: Integrate ONNX Runtime in production (API, containers, monitoring). The ONNX Runtime program runs over 3 days, delivered on site.
How is ONNX Runtime training assessed?+
Assessment relies on multiple-choice quiz to validate learning outcomes at the end of the training, continuous assessment through practical exercises and presentation of the ongoing project to the trainer. Learni issues a completion certificate together with the individual assessment report at the end of the ONNX Runtime program, which an L&D team can file as evidence.
How much does ONNX Runtime training cost per participant?+
ONNX Runtime 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 ONNX Runtime 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 ONNX Runtime 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 ONNX Runtime training?+
Python basics and introductory machine learning concepts.
Is a certificate issued after ONNX Runtime 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.
Your professional training, anywhere
Let's build your ONNX Runtime learning path.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
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