# Set up your development environment **Time to complete:** 5-10 minutes. ## What are we building? We are going to use [AWS Cloud9](https://aws.amazon.com/cloud9/) as our cloud-based integrated development environment. It will get you bootstrapped with the right tools and access on Day 1. _If you already have a Cloud9 environment, feel free to use that._ ### Step 1: Create a Cloud9 environment <details> <summary><strong>Expand if you want detailed directions</strong></summary><p> Create your Cloud9 instance by following these steps: 1. Navigate to AWS Cloud9 [in the console](https://console.aws.amazon.com/cloud9) 1. Click **Create environment** 1. Provide a name: **WildRydesIDE** 1. Click **Next step** 1. Leave all defaults 1. Click **Next step** 1. Click **Create environment** </p></details> ### Step 2: Wait for your environment to be already Your AWS Cloud9 environment is being created and your screen will look like this:  After a minute or so, your environment will be ready and you can continue. ### Step 3: Validate your environment has credentials 1. Find the "Welcome" tab and click the plus icon next to it 1. Select **New Terminal** 1. Run a command to get the caller identity: `aws sts get-caller-identity` * *This command will let you know who you are (account number, user ID, ARN)* *Hint: New editors and terminals can be created by clicking the green "+" icon in a circle*  ### Step 4: Clone this repository Let's get our code and start working. Inside the terminal: 1. Run the following command to get our code: ``` git clone https://github.com/aws-samples/aws-serverless-workshops/ ``` 1. Navigate to our workshop: ``` cd aws-serverless-workshops/MachineLearning/ ``` At this point we have built our cloud based development environment, verified it is configured with the right credentials, and copied down some source code from a code repository. ## Next step: We're ready to proceed with building the [data processing pipeline](../1_DataProcessing).