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Training ONNX Runtime 2026 - Optimizing ML Inference Multi-OS

Ref: NPB782
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 days
in-person

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Learning objectives

  • Master the installation and configuration of ONNX Runtime 2026 in professional Linux and Windows Server environments
  • Develop skills in optimizing inference performance for enterprise applications
  • Implement advanced shell scripts to automate certified ONNX Runtime deployments
  • Configure scalable inference pipelines adapted to operating system constraints
  • Integrate ONNX Runtime 2026 into hybrid architectures to boost team productivity
  • Evaluate and troubleshoot ONNX models in real enterprise production

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 1ONNX Runtime 2026 Installation: Multi-Platform Setup on Linux and Windows Server (Docker Tools, Init Scripts)

Discover the quick installation of ONNX Runtime 2026 on Linux servers via apt and Windows Server with MSI, configure CUDA and TensorRT dependencies to accelerate inference, perform practical runtime verification exercises, test compatibility of PyTorch-exported ONNX models, produce a production-ready system diagnostic report, integrate basic shell scripts for recurring automations.

Module 2Performance Optimization for ONNX Runtime 2026: CPU/GPU Tuning on Operating Systems (Benchmarks, Profiling)

Dive into graph IR optimization techniques to reduce latency by up to 40%, profile with integrated tools on Linux and Windows Server, apply dynamic and static quantization on real models, measure gains via custom benchmarks, develop shell scripts for real-time auto-monitoring, generate directly applicable tuning deliverables for enterprise, fine-tune configurations for mixed workloads.

Module 3Advanced Scripting for ONNX Runtime 2026: Linux/Windows Shell Automation (Bash, PowerShell, CI/CD)

Master shell scripting for ONNX Runtime 2026 deployment, write Linux bash scripts for conditional builds and Windows PowerShell for service orchestration, integrate GitHub Actions for hybrid CI/CD pipelines, test on concrete batch inference cases, debug runtime errors via structured logs, produce reusable templates for DevOps teams, simulate scalable deployments in interactive in-person sessions.

Module 4Enterprise Integration of ONNX Runtime 2026: APIs, Containers on Servers (Kubernetes, Docker Swarm)

Integrate ONNX Runtime 2026 into C++/Python apps via native APIs, containerize with Docker for Linux and Windows Server, deploy on Kubernetes for auto-scaling, manage high-load concurrent sessions, develop secure REST endpoints, test resilience with basic chaos engineering, deliver certified enterprise architecture blueprints, apply to real business scenarios like industrial AI vision.

Module 5Advanced Cases and Certification for ONNX Runtime 2026: Troubleshooting, System Best Practices (Final Projects)

Handle complex cases like migrating legacy models to ONNX 2026, troubleshoot memory leaks on overloaded servers, apply security best practices and Prometheus/Grafana monitoring, complete end-to-end inference final project, evaluate via quizzes and certifying practicals, receive professional skills attestation, plan post-training enterprise implementation with dedicated support.

Evaluation method

  • Daily theoretical quizzes on ONNX Runtime concepts
  • Assessed practical work through scripting and optimization exercises
  • Final multi-OS deployment project with deliverable report

Learning method

  • 70% hands-on pedagogy on dedicated Linux/Windows machines
  • Real case studies from Fortune 500 companies
  • Unlimited access to video resources and source code post-training
  • Personalized feedback in small groups of max 10

Methods, materials and delivery

The Training ONNX Runtime 2026 - Optimizing ML Inference Multi-OS 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 ML Inference Multi-OS 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 ML Inference Multi-OS 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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