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Training Mixtral - Deploying Open-Source LLMs in Production

Ref: ZTB224
10 people max.
7000€ 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 Mixtral architecture for professional AI applications
  • Develop certified fine-tuning skills for Mixtral 8x7B
  • Implement scalable Mixtral deployments in the enterprise
  • Optimize Mixtral performance with quantization and LoRA
  • Design advanced RAG pipelines integrating Mixtral
  • Deploy Mixtral on cloud for certified business use cases
  • Evaluate and monitor Mixtral models in professional 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.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Mixtral Architecture: Decoding MoE and Advanced Fine-Tuning (PyTorch, Hugging Face)

Dive into the Mixture of Experts of Mixtral 8x7B through hands-on code dissections, set up the expert environment with vLLM and Transformers, perform complete fine-tuning on customized enterprise datasets, test complex prompts to generate business insights, produce a first customized model with perplexity metrics, and validate efficiency gains on real AI optimization cases.

Module 2Mixtral Optimization: Quantization and LoRA for Enterprise Performance (bitsandbytes, PEFT)

Apply 4-bit and 8-bit quantization techniques on Mixtral to reduce latency by 70% without quality loss, integrate LoRA for ultra-efficient fine-tuning on sensitive data, experiment with practical exercises on cloud GPUs, measure memory and cost savings via concrete benchmarks, generate optimization reports ready for CTOs, and deploy a lightweight prototype for real enterprise testing conditions.

Module 3Mixtral Deployment: Inference Servers and Scaling (vLLM, Docker, Kubernetes)

Configure high-performance inference servers with vLLM and TensorRT-LLM for Mixtral, containerize via Docker for immediate scalability, orchestrate on Kubernetes with adaptive autoscaling for load peaks, simulate multi-GPU deployments through live coding, integrate secure APIs for business applications, test resilience under intense traffic, and deliver a production-ready blueprint to integrate into your enterprise AI stack.

Module 4Advanced Mixtral RAG: Retrieval and Intelligent Agents (LangChain, FAISS, LlamaIndex)

Build expert RAG pipelines fusing Mixtral with vector databases FAISS and Pinecone, integrate LangChain for autonomous agents solving complex tasks, train on internal enterprise documents for precise contextualized responses, optimize hybrid retrieval with reranking, deploy live RAG chatbots with human and automatic evaluation, analyze business accuracy gains, and produce a functional PoC for immediate demonstration to decision-makers.

Module 5Mixtral in Production: Monitoring, Security, and Business Use Cases (Prometheus, Guardrails, enterprise use-cases)

Implement comprehensive monitoring with Prometheus and Grafana for Mixtral traceability in production, secure against jailbreaks and biases via Guardrails AI, apply to concrete cases like predictive analysis or enterprise code generation, conduct GDPR compliance audits, test robustness under adversarial attacks, synthesize a decision-making dashboard with quantified KPIs, and conclude with the deployed red thread project, certifying your expert AI skills for impactful CVs.

Evaluation method

  • Expert MCQ to validate learning outcomes on Mixtral at the end of the training
  • Continuous evaluation through practical fine-tuning and deployment exercises
  • Defense of the RAG Mixtral red thread project in front of the trainer and peers

Learning method

  • Courses led by a Mistral AI expert trainer in professional practice
  • Practical exercises on real enterprise AI datasets and cases
  • Progressive red thread project for Mixtral deployment throughout the training
  • Complete course materials and source codes provided to each participant

Methods, materials and delivery

The Training Mixtral - Deploying Open-Source LLMs in Production 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 Mixtral - Deploying Open-Source LLMs 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 Mixtral - Deploying Open-Source LLMs 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

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
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« 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
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
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« 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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