Курс от CourseraIn this experience, you'll take on the role of a candidate interviewing for a Machine Learning Engineer position at a subscription streaming company. As part of the interview process, you're given a real business problem to solve: predicting which customers are about to churn, before they do. You'll build an end-to-end pipeline — exploring data, engineering features, training and evaluating a classification model, and generating churn probability predictions — using the same tools and techniques real ML teams use. Then you'll walk through your implementation in a simulated technical interview, where you'll be asked to justify your modeling choices under the kind of scrutiny a real hiring panel would apply. This experience is designed to help you build something accurate and well-structured, and to strengthen your ability to explain your reasoning clearly enough that someone else would trust it. If you're preparing for an ML Engineer interview — or want a realistic sense of whether you're ready for one — this is the fastest way to find out.
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