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

Taking Python to Production: A Professional Onboarding Guide
Taking Python to Production: A Professional Onboarding Guide

Taking Python to Production: A Professional Onboarding Guide udemy course

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

This is a course about transitioning from a "coder" to a "software engineer". It specifically covers the tools needed to develop and "ship" production-ready software with Python.


As an MLOps engineer, my role is to help enable data scientists, analysts, and junior engineers become more self-sufficient at bringing products to production.

This course covers a mix of foundational tools, engineering practices, and career advice that new engineers should be given during the onboarding process when they join a team (but they often don't get guidance!).

By the end of this course, you should feel confident contributing to complex software projects in a team setting, whether open-source or at a company (or please request a refund within 30 days!).

You will understand how closed- and open-source projects are run and how to run your own.

In the course, we write very little code and instead focus on the non-coding aspects of software engineering that make you an effective member of the software engineering community.

That said, you should have a solid grasp of Python fundamentals (loops, functions, classes, etc.) before taking this course.


Expect to learn

  • how to set up a professional Python development environment

  • how to set up a professional workflow for Python development with Visual Studio Code; extra emphasis on autocompletion

  • how to use git, GitHub, "branching strategies", and their integrations with VS Code and the terminal

  • how to write clean, maintainable code and ensure that all code contributed to your projects is good quality (testing, linting, formatting, type checking, documentation, etc.)

  • how to publish production-quality software for a wide audience with packaging, versioning, continuous integration, and continuous delivery (pre-commit, GitHub Actions, PyPI)

  • how to templatize all of the above points, so you can create new, high-quality projects in seconds

Before paying for this course, please sample the preview lectures so you can get a sense of whether it's right for you.

See you in the course!

- Eric