# Source: https://docs.kaisar.io/kaisar-network/kaisar-ai-ops/getting-started/getting-started/onboarding.md

# Onboarding

This guide will walk you through the complete onboarding process for Kaisar AI Ops.

## Initial Setup

### 1. Account Activation

After receiving your account credentials:

1. Navigate to <https://ai.kaisar.io>
2. Log in with your provided credentials
3. Update your profile information (if prompted)
4. Set up multi-factor authentication (if required)

### 2. Profile Configuration

1. Click on your profile icon (top-right corner)
2. Navigate to **Settings**
3. Update:
   * Display name
   * Email preferences
   * Notification settings
   * Time zone

### 3. Join Your Organization

1. Navigate to **Organization** in the sidebar
2. You should see your assigned organization(s)
3. Verify your role and permissions
4. Explore team members and groups

![Organization View](https://3962875474-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F01Fyr0ujWr1ipjmUOTbr%2Fuploads%2Fgit-blob-11bbb60db66284af9e1c52275f596aaa623c9cdf%2Fsection_organization_1764148155747.png?alt=media)

## Understanding Your Workspace

### Dashboard Overview

The dashboard provides:

* **Recent Activity**: Your latest experiments and deployments
* **Quick Stats**: Summary of resources and usage
* **Notifications**: System alerts and updates
* **Quick Actions**: Shortcuts to common tasks

### Navigation Structure

Familiarize yourself with the main sections:

#### Deep Learning Platform

* **Experiments**: Track ML training runs
* **Models**: Manage trained models
* **Datasets**: Organize training data

#### Deployments

* Deploy models to production
* Monitor deployment health
* Manage scaling and versions

## First Tasks

### Create Your First Experiment

1. Go to **Deep Learning Platform** → **Experiments**
2. Click **Create**
3. Configure your experiment:
   * Name and description
   * Framework (PyTorch, TensorFlow, etc.)
   * Compute resources
   * Hyperparameters
4. Submit the experiment

![Experiments View](https://3962875474-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F01Fyr0ujWr1ipjmUOTbr%2Fuploads%2Fgit-blob-4ce087d91471886f1be85b6abd1dbb8835fc23a2%2Fsection_experiments_1764148174995.png?alt=media)

### Upload a Dataset

1. Go to **Deep Learning Platform** → **Datasets**
2. Click **Create**
3. Upload your dataset or connect to external storage
4. Add metadata and tags

![Datasets View](https://3962875474-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F01Fyr0ujWr1ipjmUOTbr%2Fuploads%2Fgit-blob-67828deab295ac67e068436d89e9815175df2a88%2Fsection_datasets_1764148213987.png?alt=media)

### Register a Model

1. Go to **Deep Learning Platform** → **Models**
2. Click **Create**
3. Upload or link your trained model
4. Add version information and documentation

![Models View](https://3962875474-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F01Fyr0ujWr1ipjmUOTbr%2Fuploads%2Fgit-blob-af01ec57317f84a9468adf2d3d47fd475a3088cb%2Fsection_models_1764148186732.png?alt=media)

## Best Practices

### Organization

* Use clear, descriptive names for experiments, models, and datasets
* Add tags for easy filtering and search
* Document your work with descriptions and README files

### Collaboration

* Share experiments with team members
* Use groups to organize team access
* Comment on experiments for knowledge sharing

### Security

* Never share your credentials
* Use API tokens for programmatic access
* Review permissions regularly

## Next Steps

Now that you're onboarded:

1. Explore the [User Guide](https://github.com/Kaisar-Network/docs/blob/kaisar-ai-ops/kaisar-ai-ops/user-guide/README.md) for detailed features
2. Review [IAM & Security](https://github.com/Kaisar-Network/docs/blob/kaisar-ai-ops/kaisar-ai-ops/user-guide/iam-security.md) for access management
3. Check [Troubleshooting](https://docs.kaisar.io/kaisar-network/kaisar-ai-ops/troubleshooting/troubleshooting) for common issues

## Getting Help

If you need assistance:

* Check the [FAQ](https://docs.kaisar.io/kaisar-network/kaisar-ai-ops/troubleshooting/troubleshooting/faq)
* Contact your team administrator
* Reach out to [Support](https://docs.kaisar.io/kaisar-network/kaisar-ai-ops/troubleshooting/troubleshooting/support)