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machine-learning-devops-engineer-nanodegree-udacity

Overview

The Machine Learning DevOps Engineer Nanodegree program focuses on the software engineering fundamentals needed to successfully streamline the deployment of data and machine-learning models in a production-level environment. Students will build the DevOps skills required to automate the various aspects and stages of machine learning model building and monitoring over time.

Educational Objectives:

Students who graduate from the program will be able to:

  • Implement production-ready Python code/processes for deploying ML models outside of cloud-based environments facilitated by tools such as AWS SageMaker, Azure ML, etc.
  • Engineer automated data workflows that perform continuous training (CT) and model validation within a CI/CD pipeline based on updated data versioning
  • Create multi-step pipelines that automatically retrain and deploy models after data updates
  • Track model summary statistics and monitor model online performance over time to prevent model-degradation

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