MLOps

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Machine Learning Operations 1 (MLOps1-GCP): Deploying AI & ML Models in Production using Google Cloud Platform (GCP) (edX)

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we [...]

Machine Learning Operations 1 (MLOps1-AML): Deploying AI & ML Models in Production using Microsoft Azure Machine Learning (AML) (edX)

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we [...]

Machine Learning Operations 1 (MLOps1-AWS): Deploying AI & ML Models in Production using Amazon Web Services (AWS) (edX)

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we [...]

Machine Learning Operations 2 (MLOps2-AML): Data Pipeline Automation & Optimization using Microsoft Azure Machine Learning (AML) (edX)

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how to automate your pipeline’s functions and continuously optimize its performance, which is why we developed this course, MLOps2: Data [...]

Machine Learning Operations 2 (MLOps2-GCP): Data Pipeline Automation & Optimization using Google Cloud Platform (GCP) (edX)

Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how to automate your pipeline’s functions and continuously optimize its performance, which is why we developed this course, MLOp2s: Data [...]

MLOps for Scaling TinyML (edX)

This course introduces learners to Machine Learning Operations (MLOps) through the lens of TinyML (Tiny Machine Learning). Learners explore best practices to deploy, monitor, and maintain (tiny) Machine Learning models in production at scale.