Build a Linux development environment on Windows with WSL, then run an RServe web service with a sidecar container on Minikube as the example app.

Develop and test AWS applications against LocalStack, a mocking framework that runs AWS services on a local machine, demonstrated with a web service.

Host the web application that calls an R machine learning model on Amazon S3, so both the front end and the Lambda backend run without a server.

Expose an R machine learning model packaged in AWS Lambda through Amazon API Gateway, giving the model a callable HTTP endpoint on AWS.

Deploy an R machine learning model to AWS Lambda and call it without managing a server.

Package a logistic regression model built in R so it can run on AWS Lambda, after testing it locally.

Wrap Python boto calls for Amazon S3 in an R package, rs3helper, where the Python scripts return JSON so R parses it as vectors and data frames.

Call a SOAP web service from Python with the suds library, a job R has no comprehensive client package for, demonstrated on the Sizmek MDX API.

Write Python in an object-oriented style, shown with SOAP API client classes, and a reading order for the Introducing Python book by chapter group.