Intermediate

W&B Advanced: Introduction

Go beyond basic experiment tracking. Learn the advanced W&B features that power ML teams at scale.

Beyond Experiment Tracking

The W&B Basics course covered experiment tracking, basic sweeps, and artifacts. This advanced course dives into the features that make W&B a complete ML platform for teams.

What We'll Cover

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Reports

Interactive documents that combine live visualizations, tables, and markdown. Share experiment findings with stakeholders, create reproducible analyses, and build team knowledge bases.

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Tables

Log structured data for deep analysis. Compare model predictions side-by-side, visualize dataset distributions, and build interactive data exploration workflows.

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Advanced Sweeps

Multi-objective optimization, early termination strategies, distributed sweeps across clusters, and custom sweep agents for complex search spaces.

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Launch

Submit and manage training jobs across any compute backend - Kubernetes, AWS SageMaker, GCP Vertex AI, or local Docker containers.

Who Is This For?

  1. ML Engineers in teams

    Who need to communicate results, coordinate experiments, and manage shared compute resources.

  2. Data Scientists scaling up

    Moving from notebooks to production workflows with proper experiment management and reproducibility.

  3. ML Platform Engineers

    Building internal ML platforms and need to integrate W&B into CI/CD pipelines and compute infrastructure.

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Prerequisites: Complete the W&B Basics course or have working knowledge of W&B experiment tracking, artifacts, and basic sweeps. You should be comfortable with wandb.init(), wandb.log(), and the W&B dashboard.

Ready to Go Deeper?

Live instructor-led courses from our partners. Affiliate disclosure.