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Training Weights & Biases 2026 - Mastering Advanced MLOps in AI

Ref: JIA675
10 people max.
4400€ 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 advanced sweeps in Weights & Biases 2026 to optimize hyperparameters in certified professional training
  • Develop secure collaborative pipelines to strengthen enterprise MLOps skills
  • Design automated reports and interactive dashboards for high-performance predictive analysis
  • Implement integrations with Kubeflow and Ray to scale professional AI workflows
  • Optimize production monitoring with intelligent alerts and advanced versioning
  • Deploy models in edge computing via Weights & Biases 2026 for certified applications
  • Acquire expert team collaboration skills for enterprise AI projects

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 1Advanced Fundamentals of Weights & Biases 2026: Sweeps and Optimized Logging (PyTorch, TensorFlow, Practical Exercises)

Discover the new APIs of Weights & Biases 2026 for real-time metric logging, configure hyperparameter sweeps on complex datasets, practice with PyTorch and TensorFlow via concrete CNN optimization cases, generate your first automated reports, test Git integration for smooth versioning, and produce a deliverable: personalized dashboard tracking 10 parallel experiments in under an hour.

Module 2Collaborative Pipelines in Weights & Biases 2026: Teams and Shared Projects (Kubeflow, Ray, Collaborative Workshops)

Dive into Weights & Biases 2026 multi-team workspaces, integrate Kubeflow to orchestrate end-to-end pipelines, deploy Ray for distributed scaling on GPU clusters, conduct practical workshops in pairs on real enterprise projects, configure RBAC for secure access, visualize model artifacts in 3D, and validate with a deliverable: shared collaborative project with full history and granular permissions.

Module 3Monitoring and Production in Weights & Biases 2026: Alerts and Deployment (Prometheus, Edge Computing, Live Simulations)

Master advanced monitoring with AI-predictive alerts in Weights & Biases 2026, integrate Prometheus for custom metrics, simulate production deployments on Kubernetes, optimize for edge devices with TensorRT, analyze model drifts in real-time via interactive dashboards, practice automatic rollback on failures, and create a deliverable: alert system configured for a production NLP model detecting 95% of anomalies.

Module 4Expert Optimization in Weights & Biases 2026: Reports and Global Scaling (Custom API, Enterprise Cases, Certification Project)

Push the limits with custom APIs in Weights & Biases 2026 for advanced automations, generate executive multi-model reports, scale on AWS SageMaker and GCP Vertex AI, apply to real industry cases like predictive finance, review MLOps best practices in groups, integrate feedback loops for rapid iterations, and finalize with a certifying deliverable: complete portfolio of 5 optimized projects ready for professional CV.

Evaluation method

  • Daily technical quiz on Weights & Biases 2026 features (minimum 80% success rate)
  • Final collaborative project evaluated by MLOps experts (report and dashboard deliverables)
  • 360° feedback and self-assessment of acquired enterprise skills

Learning method

  • 70% hands-on approach: practical workshops on real datasets and open-source tools
  • Agile methods: short iterations with immediate feedback from certified trainers
  • Enterprise case studies: reproducing pipelines from AI leaders like OpenAI
  • Post-training support: 3 months access to Weights & Biases platform and alumni community

Methods, materials and delivery

The Training Weights & Biases 2026 - Mastering Advanced MLOps in AI 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 Weights & Biases 2026 - Mastering Advanced MLOps in AI 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 Weights & Biases 2026 - Mastering Advanced MLOps in AI 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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