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Training Qwen - Developing High-Performing Generative AIs

Ref: KTG560
10 people max.
5600€ 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
4 journées
distanciel

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Learning objectives

  • Master Qwen architectures for professional, certifiable AI applications
  • Develop skills in fine-tuning Qwen tailored to business needs
  • Implement RAG pipelines with Qwen for optimized content generation
  • Design and deploy autonomous AI agents based on Qwen in production
  • Optimize Qwen performance via quantization and distillation for scalability
  • Integrate Qwen into DevOps workflows for secure deployments
  • Evaluate and monitor Qwen models in real professional contexts

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 1Qwen Architecture: Advanced Fine-Tuning and Customization (PyTorch, LoRA, Enterprise Datasets)

Dive into the specifics of Qwen 72B models and variants, install the environment with Hugging Face and vLLM, perform initial fine-tuning on customized sectoral datasets via LoRA and QLoRA to minimize resources, test performance on benchmarks like MMLU and GSM8K, produce your first customized model with quantitative evaluation, apply data augmentation techniques for immediate professional results.

Module 2Advanced Qwen Pipelines: RAG and Intelligent Agents (LangChain, Vector Stores, Custom Tools)

Build high-performing RAG systems with Qwen by integrating FAISS and Pinecone for vector retrieval, chain advanced prompts via LangChain for contextual generation, develop multi-tool agents capable of reasoning and executing complex tasks like code analysis or automated research, simulate real business use cases with feedback loops, generate tested functional deliverables live, optimize latency for seamless integration into your applications.

Module 3Qwen Optimization: Quantization and Scalable Deployment (vLLM, TensorRT-LLM, Kubernetes)

Master 4-bit and 8-bit quantization on Qwen to reduce GPU memory by 75% without loss of precision, deploy via vLLM and TensorRT-LLM for ultra-fast inference, configure secure API servers with authentication and rate limiting, integrate into Kubernetes for high availability, measure impact via metrics like tokens/second and energy cost, produce a production-ready CI/CD deployment pipeline, apply security best practices against jailbreaks and data leaks.

Module 4Enterprise Qwen Applications: Monitoring and Scaling (Prometheus, Business Cases, Ongoing Project)

Integrate Qwen into business workflows like intelligent chatbots or predictive analysis, monitor in real-time with Prometheus and Grafana to detect drifts, scale horizontally on multi-node GPU clusters, evaluate ROI via A/B testing on business metrics, finalize your ongoing project with full deployment and documentation, share experience feedback for skill certification, leave with a concrete portfolio valuable in the enterprise.

Evaluation method

  • Expert multiple-choice quiz on Qwen architectures and optimization
  • Practical evaluation through fine-tuning and deployment of an AI agent
  • Defense of the ongoing project with performance analysis and ROI

Learning method

  • Courses led by a certified AI expert in Qwen production
  • Practical exercises on GPU clusters with real business cases
  • Personalized evolving ongoing project over 4 days
  • Detailed course materials and source codes provided to participants

Methods, materials and delivery

The Training Qwen - Developing High-Performing Generative AIs 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 Qwen - Developing High-Performing Generative AIs 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 Qwen - Developing High-Performing Generative AIs 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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