Ensure you have an AWS account and have created an S3 bucket where you will store the data. Note the bucket name and region for future use. Ensure your IAM user has the necessary permissions to access S3 and upload objects.

Install Python on your local machine if it isn't already installed. Ensure you have pip, Python's package installer, to install necessary libraries. Use `pip install boto3 requests` to install Boto3 (AWS SDK for Python) and the Requests library for making HTTP requests.

Write a Python script that will make GET requests to the public API. Use the Requests library to handle the HTTP connection. Parse the JSON response or the appropriate format that the API returns.

```python
import requests

def fetch_data(api_url):
response = requests.get(api_url)
if response.status_code == 200:
return response.json() # or response.text for non-JSON APIs
else:
raise Exception(f"Failed to fetch data: {response.status_code}")
```

Depending on the API response, you may need to process the data into a format suitable for storage. This could involve converting JSON to a CSV or plain text file, or simply saving the JSON response as-is.

```python
import json

def prepare_data(data):
# Example: convert dictionary to JSON string
return json.dumps(data)
```

Configure your AWS credentials locally so that Boto3 can authenticate with AWS services. You can do this by running `aws configure` in your terminal and entering your AWS Access Key ID, Secret Access Key, default region, and output format.

Use Boto3 to upload your processed data to the S3 bucket. Create a function that takes the data and uploads it as an object in your S3 bucket.

```python
import boto3

def upload_to_s3(data, bucket_name, object_name):
s3_client = boto3.client('s3')
s3_client.put_object(Bucket=bucket_name, Key=object_name, Body=data)

```

If you need to move data regularly, automate the process using a scheduler. On a Unix system, you can use `cron` jobs to run your script at regular intervals. On Windows, you can use Task Scheduler. Ensure the script is executable and has the necessary environment configurations to run without manual intervention.

```sh
# Example cron job to run every day at midnight
0 0 /usr/bin/python /path/to/your/script.py
```

By following these steps, you can efficiently move data from public APIs to your S3 bucket without relying on third-party connectors, maintaining control over the process and customization.