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Training TensorRT-LLM - Accelerate LLM Inference in Production

Ref: RQD582
10 people max.
From $4,620 HT / per person
Pay in 3 installments · On-site on request · +$540 with certification exam
4 days
Remote

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Learning objectives

  • Master TensorRT-LLM to optimize LLM inference in enterprise settings
  • Develop high-performance and scalable inference engines
  • Implement quantization techniques and layer fusion
  • Design TensorRT-LLM serving pipelines with Triton Inference Server
  • Optimize latency and throughput for certified production deployments
  • Deploy accelerated LLM applications on professional NVIDIA GPUs

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.

Célian Lebacle
Célian Lebacle

Learni trainer · Web & mobile expert

73%productivity gap
×3cost of inaction

Program

Module 1TensorRT-LLM Fundamentals: Installation and First Engine Builds (NVIDIA Docker, LoRA, Containers)

Quick installation of the TensorRT-LLM environment on NVIDIA GPUs via official Docker containers, hands-on with build tools to convert Hugging Face models into optimized engines, practical exercises on Llama and Mistral with FP8 and AWQ quantization, creation of your first functional engine, real-time latency tests, and performance gain analysis for concrete enterprise use cases.

Module 2Basic TensorRT-LLM Optimizations: Layer Fusion and KV Cache (Plugins, Multi-Head Attention)

Exploration of TensorRT-LLM's automatic optimization passes such as GEMM fusion and multi-head attention, manual implementation of plugins for custom KV cache, exercises on LLMs from 7B to 70B parameters with paging and prefix caching, precise acceleration measurements via TensorRT benchmarks, development of a reusable build script for professional projects, and group validation of deliverables.

Module 3Advanced TensorRT-LLM Techniques: Serving and Scaling (Triton, Multi-GPU, Dynamic Batching)

Integration of TensorRT-LLM with Triton Inference Server for scalable serving, multi-GPU configuration with tensor parallelism and pipeline parallelism, implementation of dynamic batching and in-flight batching to handle variable requests, practical cases on enterprise chatbots with token streaming, GPU resource optimization using NVIDIA DCGM tools, and production of actionable monitoring metrics.

Module 4Production Deployment of TensorRT-LLM: Monitoring and Real Cases (Kubernetes, Security, CI/CD)

Deployment in Kubernetes clusters using Helm charts for TensorRT-LLM, securing endpoints with TLS and rate limiting, CI/CD integration via GitHub Actions for automated engine rebuilds, resolution of real-world issues like OOM and performance drift, final red thread project on a customized LLM in simulated production, delivery of performance reports, and action plan for certified enterprise skills.

Evaluation method

  • Multiple-choice quiz to validate learning outcomes at the end of the training
  • Continuous assessment via practical TensorRT-LLM exercises
  • Presentation of the red thread LLM optimization project

Learning method

  • Courses led by an active NVIDIA expert trainer
  • Hands-on exercises on real enterprise LLMs
  • Progressive red thread project on TensorRT-LLM
  • Complete course materials provided to each participant

Methods, materials and delivery

The Training TensorRT-LLM - Accelerate LLM Inference in Production 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 TensorRT-LLM - Accelerate LLM Inference in Production 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 TensorRT-LLM - Accelerate LLM Inference in Production 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 TensorRT-LLM - Accelerate LLM Inference in Production training cost?+
The individual price is $4,620 (USD). A detailed quote is sent within one business day.
How long is the Training TensorRT-LLM - Accelerate LLM Inference in Production training?+
The training lasts 4 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?+
Mastery of Python, PyTorch or TensorFlow, basics in LLMs and CUDA
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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