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docs/getting_started/ds/ds_first_steps.md

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+---
+title: First Steps
+---
+
+
+## Install ClearML
+
+First, [sign up for free](https://app.community.clear.ml)
+
+Install the clearml python package:
+```bash
+pip install clearml
+```
+
+Connect your computer to the server by [creating credentials](https://app.community.clear.ml/profile), then run the below and follow the setup instructions:
+```bash
+clearml-init
+```
+
+
+## Auto-log experiment
+
+In ClearML, experiments are organized as [Tasks](../../fundamentals/task). 
+
+ClearML will automatically log your experiment and code once you integrate the ClearML [SDK](../../clearml_sdk.md) with your code.
+At the begging of your code, import the clearml package 
+
+```python
+From clearml import Task
+```
+
+:::note
+To ensure full automatic logging it is recommended to import the ClearML package at the top of your entry script.
+:::
+
+Then initialize the Task object in your `main()` function, or the beginning of the script.
+
+```python
+Task = Task.init(project_name=”great project”, task_name=”best experiment”)
+```
+
+Task name is not unique, it's possible to have multiple experiments with the same name.
+If the project does not already exist, a new one will be created automatically.
+
+
+**That’s it!** You are done integrating ClearML with your code :)
+
+Now, [command-line arguments](../../fundamentals/hyperparameters.md#argument-parser), [console output](../../fundamentals/logger#types-of-logged-results) as well as Tensorboard and Matplotlib will automatically be logged in the UI under the created Task.
+<br/>
+
+Sit back, relax, and watch your models converge :) or continue to see what else can be done with ClearML [here](ds_second_steps.md).
+