Setting Up AWS and Serverless for Data Science Projects

Setting up a local environment for serverless data science can be daunting, but a robust configuration is the foundation of successful cloud deployments. This course guides you through configuring and verifying your AWS and Serverless Framework setups, ensuring your machine learning models and data pipelines run flawlessly in the cloud. What you'll learn: - Understand the core concepts of serverless computing and cloud-based data science pipelines. - Configure the AWS CLI securely using modern identity and access management guidelines. - Install and verify the Serverless Framework for deploying Python-based functions. - Manage Python dependencies and virtual environments specifically optimized for AWS Lambda. - Test your local serverless configuration with a basic data processing script. - Troubleshoot common credential, permission, and deployment issues before launching large-scale projects. You will start with foundational cloud concepts, progress through step-by-step CLI and framework configurations, and wrap up with hands-on verification exercises to ensure your environment is fully operational. This course is designed for aspiring data scientists, analysts, and developers who are new to serverless architecture and want a rock-solid local setup. No prior AWS experience is required. Start building your serverless data science foundation today.