Taking Python to Production: A Professional Onboarding Guide

Data scientists, analysts, and beginner devs: transition from "coder" to "software engineer" and learn to ship code

Created by: Eric Riddoch
Instructor | ML Platform Lead Engineer

What Will I Learn?

• Set up a professional Python development environment - Visual Studio Code, pyenv, git, autocompletion
• Learn the professional git workflow with GitHub and CI/CD with GitHub Actions
• Make the terminal more intuitive with ZSH and plugins
• Version and package Python software and publish it for the community
• Setup automated code quality checks (testing, linting, documentation, type checking, etc.)

Requirements

• Basic Linux/bash knowledge: cp, mv, ls, rm, etc;
• A computer that supports a *native* Linux terminal. If you are running on MacOS or Linux, you're good. If you are running Windows 10 or 11, we'll cover how to install the WSL 2 (See the early Windows videos).
• Knowledge of Python syntax: loops, functions, classes, etc.
• Comfortable Googling errors to get unstuck

Target audience

• Lower-intermediate to advanced Python developers who meet the requirements and are interested in the learning outcomes.
• Data scientists, analysts, junior developers, and self-taught developers who want want to set up a development environment for writing "production-ready" software