# Project and Dataset

- [Create](/data-organization/project-dataset/create.md): This article provides a step-by-step guide to creating classes and tags: how to define them in the project before annotation and how to add them directly in the labeling tools.
- [Data Structure](/data-organization/project-dataset/data-structure.md): This article explains the Data structure in Supervisely, including how Projects, Datasets, and Files are organized in Team and Workspace. Learn how to navigate, manage, and structure your data.
- [Define Classes & Tags](/data-organization/project-dataset/define-classes-tags.md): This article explains how to create and manage classes and tags for data annotation in the Labeling Tool to ensure structured and consistent labeling within a project.
- [Gallery & Table views](/data-organization/project-dataset/gallery-table-views.md): This article is about how gallery and table views let you customize data display: gallery provide a quick visual overview, while tables offer detailed, sortable comparisons.
- [Collections](/data-organization/project-dataset/collections.md): Collections are custom selections of data within a project. They enable flexible filtering and control over annotation workflows.
- [Project Versions](/data-organization/project-dataset/project-versions.md): Learn how to use Project Versions in Supervisely. Save, restore, and track project states, instantly preview data, and visualize data evolution with MLOps Workflow.
- [AI Search](/data-organization/project-dataset/ai-search.md): This article is about AI Search, which quickly finds images using semantic similarity powered by CLIP. It supports prompt-based and diverse search modes with automatic embedding updates.
- [Quality Assurance & Statistics](/data-organization/project-dataset/quality-assurance-and-statistics.md): Understanding your data's characteristics is a key aspect of data preparation. The Statistics section provides tools for data analysis, calculation of statistical metrics and data visualization.
- [Practical applications of statistics](/data-organization/project-dataset/quality-assurance-and-statistics/practical-applications-of-statistics.md): Learn how to use best quality assurance and interactive statistical tools to perfect your custom training datasets and improve neural network performance.
- [Project Settings](/data-organization/project-dataset/project-settings.md): Configure project-level settings in Supervisely, including the labeling interface and Read-only mode to protect your data from accidental changes.
- [Advanced](/data-organization/project-dataset/advanced.md)
- [Custom Data](/data-organization/project-dataset/advanced/custom-data.md): Explore how to store and manage technical metadata, configurations, and integration settings using Custom Data in JSON format.
- [Validation Schemas](/data-organization/project-dataset/advanced/validation-schemas.md)