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!
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