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Training ONNX Runtime 2026 - Optimizing High-Performance ML Inference

Ref: NSF209
10 people max.
5500€ 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
5 journées
distanciel

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Learning objectives

  • Master the fundamentals of ONNX Runtime 2026 in a certified professional training.
  • Develop skills to convert and execute optimized ML models.
  • Implement fast inferences on various hardware in a business context.
  • Optimize ONNX Runtime performance for real-world applications.
  • Design scalable and secure inference pipelines.
  • Acquire practical skills to boost team productivity.
  • Prepare for a recognized certification in professional ONNX skills.

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 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.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Introduction to ONNX Runtime 2026: Installation and First Models (Python, ONNX Basics)

Discover ONNX Runtime 2026 through guided installation on Windows, Linux, and mobile, set up the Python environment with pip and conda, convert your first TensorFlow or PyTorch models to standardized ONNX format, run simple inferences on MNIST datasets, analyze outputs with integrated visualizations, and generate an initial performance report to validate the basics in just a few hours of intensive practice.

Module 2ONNX Runtime 2026: Basic Inference and CPU Optimization (Sessions, Providers)

Dive into ONNX Runtime 2026 inference sessions, configure CPU providers for smooth execution, test image classification models with OpenCV, measure latency and throughput using built-in benchmarks, apply pre-processing techniques to accelerate pipelines, complete exercises on real cases like object detection, and generate comparative charts to demonstrate immediate speed gains in a business setting.

Module 3ONNX Runtime 2026: GPU and Hardware Acceleration (CUDA, DirectML)

Explore GPU acceleration with ONNX Runtime 2026 using CUDA and TensorRT providers, deploy models on NVIDIA GPUs for ultra-fast inferences, integrate DirectML for Windows edge devices, practice on COCO datasets for object detection, optimize memory with dynamic quantization, simulate production scenarios in groups, and produce deliverables like a GPU inference script ready for integration into scalable ML applications.

Module 4ONNX Runtime 2026: Advanced Models and Integration (Web, Mobile, Edge)

Integrate ONNX Runtime 2026 into web apps with JavaScript and ONNX.js, deploy on Android/iOS mobile via ONNX Runtime Mobile, test edge computing on Raspberry Pi, manage multi-models in parallel sessions, apply security with input encryption, develop a complete real-time speech recognition project, and validate cross-platform performance for robust and reliable enterprise deployments.

Module 5ONNX Runtime 2026: Expert Optimization and Certification (Profiling, Deployment)

Master advanced profiling of ONNX Runtime 2026 with trace tools and graph optimization, reduce model size via INT8 quantization, deploy in production with Docker/Kubernetes, simulate high loads for scalability, review all concepts via interactive MCQs, prepare for Qualiopi certification with a project portfolio, and leave with skills ready to boost your enterprise ML projects.

Evaluation method

  • Daily interactive quizzes on ONNX Runtime 2026 to validate learning outcomes.
  • Practical projects evaluated by expert trainers at the end of the training.
  • Final certifying exam with MCQs and real-world cases for professional skills.

Learning method

  • 70% hands-on pedagogy on ONNX Runtime 2026 with practical exercises.
  • Groups limited to 10 for personalized in-person support.
  • Real business case studies for immediate skill application.
  • 3-month post-training support with resources and dedicated forum.

Methods, materials and delivery

The Training ONNX Runtime 2026 - Optimizing High-Performance ML Inference 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 Training ONNX Runtime 2026 - Optimizing High-Performance ML Inference 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 2026 - Optimizing High-Performance ML Inference 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
★★★★★

« 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
★★★★★

« 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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