Data Science in Production: Building Scalable Model Pipelines

Gain insights into building scalable data and model pipelines, explore different cloud environments, delve into streaming workflows, and discover essential tools for creating real-time data products.

4.5

110 Lessons

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The goal of this course is to provide you with a set of tools that can be used to build predictive model services for product teams. In this course, you’ll start by covering the different cloud environments and tools for building scalable data and model pipelines. You’ll then learn the different data sets and types of models that will be used heavily in everyday production. Throughout the course, you’ll have plenty of exercises and challenges to get you comfortable working with the diverse toolset. Lastly, you’ll explore streaming model workflows which is crucial for building real-time data pipelines that move data between different components in a cloud environment. After working through this course, you will have gained valuable hands-on experience with many of the tools needed to build data products. You will also have a better understanding of how to build scalable machine learning pipelines in a cloud environment.

The goal of this course is to provide you with a set of tools that can be used to build predictive model services for product te...Show More

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Course Author:

Ben Weber

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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