ML Engineering focuses on the practical aspects of deploying and maintaining machine learning models in real-world applications. Whether you're interested in automating data pipelines with tools like Python and GitHub Actions, or deploying ML solutions using FastAPI, Docker, and AWS, the videos here equip developers and aspiring data scientists with the skills they need. You'll learn foundational concepts and key skills necessary to thrive in the field, like those outlined in '4 Skills You Need to Be a Full-Stack Data Scientist'.
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![Automating Data Pipelines with Python & GitHub Actions [Code Walkthrough]](https://img.youtube.com/vi/wJ794jLP2Tw/mqdefault.jpg)
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The third AI workshop taught by our legendary teacher, Nick Sarafa. This is a full-day hands-on training workshop for purposeful co-creation with AI using Claude Code. Imagine having access to hundreds of billions of dollars of computing power and knowing exactly how to make it work for you through the power of super intelligence.
Let us build it for you. Design and engineering from the people who shipped platforms to billions of users. AI-native, live in weeks, and yours outright at the end.
One a week, never sold on, and one click to stop.
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