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Training Vertex AI - Orchestrating Scalable ML Pipelines

Ref: EPA981
10 people max.
3675€ 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
3 journées
distanciel

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Learning objectives

  • Master Vertex AI to orchestrate professional ML pipelines in enterprise
  • Develop and scale distributed training workflows with Vertex AI
  • Implement advanced MLOps via Vertex AI Pipelines and Workbench
  • Optimize hyperparameter tuning and AutoML on Vertex AI
  • Deploy high-performing AI models with integrated monitoring
  • Integrate Vertex AI into hybrid cloud architectures for certification
  • Acquire skills for secure production deployments

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 1Vertex AI Architecture: Setting up Environments and Initial Pipelines (Workbench, Kubeflow, Custom Components)

Dive into Vertex AI architecture by setting up Vertex AI Workbench notebooks for reproducible and collaborative experiments, develop your first Kubeflow pipelines with custom components adapted to real enterprise datasets, test automated orchestration on GPU/TPU, produce versioned artifacts and traceability reports, practical exercises on concrete prediction cases with live code review for immediate skills advancement.

Module 2Vertex AI Training: Hyperparameter Tuning and Advanced AutoML (Training Jobs, Hyperparameter Tuning Service)

Optimize your ML models via distributed training jobs on Vertex AI, explore the automatic tuning service to accelerate convergence on massive datasets, integrate AutoML Tables and Vision for high-performing baselines without excessive coding, experiment with advanced feature engineering strategies using BigQuery ML, generate precise metrics and exportable models, hands-on workshops on real-time optimization for performance gains up to 30% in professional production.

Module 3Vertex AI MLOps Deployment: Serving, Monitoring, and CI/CD (Prediction Endpoints, Model Monitoring, Vertex AI Pipelines)

Master model deployment via Vertex AI Prediction for scalable and serverless endpoints, set up automated monitoring for drifts and performance with custom alerts, implement end-to-end CI/CD pipelines integrating Git and Cloud Build, test resilience with A/B testing and canary releases on real traffic, produce a red thread project deployed with Grafana dashboards, focus on security and GDPR compliance for certified and reliable enterprise applications.

Evaluation method

  • Advanced technical MCQ on Vertex AI at the end of the training
  • Evaluation through practical exercises and developed pipelines
  • Defense of the MLOps red thread project with expert feedback

Learning method

  • Sessions led by active Google Cloud certified trainers
  • Practical exercises on real enterprise cases and open-source datasets
  • Progressive red thread project deployed live on Vertex AI
  • Detailed course materials, replay videos, and GCP resources

Methods, materials and delivery

The Training Vertex AI - Orchestrating Scalable ML Pipelines 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 Vertex AI - Orchestrating Scalable ML Pipelines 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 Vertex AI - Orchestrating Scalable ML Pipelines 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

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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
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« 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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