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Training Vision-language models - Mastering Multimodal AI in the Enterprise

Ref: IDI122
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 architectures of Vision-language models for professional certifying projects.
  • Develop skills in fine-tuning VLMs tailored to business needs.
  • Implement MLOps pipelines to deploy Vision-language models effectively.
  • Design multimodal applications combining vision and language with TensorFlow and PyTorch.
  • Optimize VLM performance for scalable integration into production.
  • Evaluate and deploy AI solutions based on Vision-language models in a professional context.

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 1Vision-language models: Fundamentals and Key Architectures (TensorFlow, PyTorch)

Discover the principles of Vision-language models through theoretical and practical modules, exploring CLIP, BLIP, and Flamingo with multimodal datasets like LAION or COCO. Perform joint vision-text encoding exercises, analyze multimodal transformers, and produce your first cross-embeddings for classification tasks, all in interactive remote format for rapid assimilation of essential skills.

Module 2Vision-language models: Fine-tuning and Domain-Specific Adaptation (PyTorch)

Dive into fine-tuning VLMs on real business cases. Use Hugging Face Transformers to adapt pre-trained models to your custom visual and textual data, implement LoRA and QLoRA techniques to optimize resources, test on benchmarks like VQA or captioning, generate performance reports, and deploy a functional prototype ready for professional integration.

Module 3Vision-language models: Advanced Multimodal Tasks (TensorFlow, PyTorch)

Explore advanced applications of Vision-language models for visual search, description generation, and zero-shot learning. Code pipelines with TensorFlow for retrieval and PyTorch for generation, work on real datasets like Visual Genome, evaluate with FID and BLEU metrics, collaborate in live sessions to solve business challenges, and deliver a complete optimized notebook.

Module 4Vision-language models: MLOps Integration and Scalable Deployment

Integrate Vision-language models into professional MLOps workflows using Docker, Kubernetes, and MLflow. Set up inference servers with TensorRT and ONNX, automate CI/CD pipelines for multimodal model monitoring, test latency on cloud GPUs, manage model versions for the enterprise, and produce a fully functional end-to-end deployment with performance monitoring dashboards.

Module 5Vision-language models: Real Projects and Production Optimization (MLOps)

Carry out a capstone project on a business application like medical image analysis or e-commerce using Vision-language models. Optimize for efficiency with distillation and pruning, integrate secure APIs, evaluate business impact via simulated ROI, present your solution in a professional pitch, receive certifying feedback, and leave with a concrete portfolio to boost your career in multimodal AI.

Evaluation method

  • Interactive quizzes and MCQs at the end of each module to validate theoretical knowledge.
  • Hands-on practical projects evaluated by MLOps experts.
  • Real case study with oral presentation and certifying technical report.

Learning method

  • Active pedagogy with 70% hands-on practice on real code and professional datasets.
  • Live remote sessions in small groups for personalized follow-up.
  • Unlimited resources: notebooks, videos, post-training forums.
  • Expert 1-to-1 mentoring to resolve your specific challenges.

Methods, materials and delivery

The Training Vision-language models - Mastering Multimodal AI in the Enterprise 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 Vision-language models - Mastering Multimodal AI in the Enterprise 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 Vision-language models - Mastering Multimodal AI in the Enterprise 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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