I have a CSV of player data sitting in CSV file, and I need a straightforward, working prototype that turns that raw file into a usable machine-learning pipeline. Here is the flow I’m after: 1. AWS Lambda • Triggered based on s3 event to pull the CSV from S3. • Perform data cleaning, data transformation, and data aggregation in-memory. • Write the processed output back to an Amazon RDS. 2. AWS Step Functions + Amazon SageMaker • Orchestrate a small two-step pipeline: basic feature-engineering script followed by a Scikit-Learn training job. • Keep it modular so I can swap in new CSVs or tweak hyper-parameters later. What I expect from you • A concise, well-commented Lambda function (Python preferred) and an IAM policy snippet I can paste into my account. • A Step Functions state machine definition (Amazon States Language) that wires up the Lambda preprocessing step with the SageMaker processing and training jobs. • A README that walks me through one-click (or nearly so) deployment using the AWS CLI or SAM. Given the limited budget, I’m looking for a minimal yet functional blueprint—something I can run end-to-end today and extend on my own later. If you have questions about my AWS setup, let me know and we’ll keep it simple.