Python is perhaps the bread-and-butter coding language for data scientists and ML practitioners, but the advantages of becoming a programming polyglot are as clear as ever. The projects that data teams work on cross platforms and architectures, and having the ability to switch to less common—but sometimes more efficient—languages is usually a powerful advantage.

For our highlights this week, we selected recent articles that cover plenty of ground: they give attention to a big selection of languages, projects, and workflows. These posts invite you to roll up your proverbial sleeves and begin tinkering with some code—they usually might just encourage you to expand your knowledge even further.