MLOps Fundamentals

This self-paced course introduces absolute beginners to MLOps — the practices for reliably building, deploying, monitoring, and maintaining machine learning models in the real world — anchored on the relatable "it works on my laptop" problem. It builds understanding step by step through the 5-stage ML lifecycle loop, the concept of model "drift," the five pillars, three maturity levels, the people and industries involved, and a tools-by-stage toolbox. Strong emphasis is placed on the core mindset shift that deployment is the start of a model's life, not the finish, reinforced through best practices, common pitfalls, and practical tips. It closes hands-on with two quizzes, four no-coding exercises, a paper-based capstone to design a full pipeline, a printable takeaways slide, and a glossary cheat-sheet.