Data Science in Production: Building Scalable Model Pipelines
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Learn to build scalable model pipelines for data science in production, focusing on best practices for data handling and model deployment.
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.
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