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Training ONNX Runtime - Deploy Optimized AI Models

Ref: HHN721
10 people max.
From $3,465 HT / per person
Pay in 3 installments · On-site on request · +$540 with certification exam
3 days
Remote

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Learning 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

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.

Imed BEN AMOR
Imed BEN AMOR

Learni trainer · Development expert

73%productivity gap
×3cost of inaction

Program

Module 1Fundamentals: 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 2Optimization: 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 3Deployment: 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.

Evaluation method

  • 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

Learning method

  • 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

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.

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.

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 and introductory machine learning concepts
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

This training across cities

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