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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Your idea can be anything. At our last workshops, people built plant-based nutrition businesses, a way to measure planetary resilience, crochet headwear and a way to connect lonely people living in the same building. An asset manager went on to raise an additional £25M on their fund within nine months. The fourth workshop is a full day at KOKO with Nick Sarafa, learning to build with Claude Code. Bring the thing you keep meaning to start. We’ll bring the pizza.
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