Designing and Implementing a Data Science Solution on Azure

Enrollment is Closed

About this course

Candidates for this course should have subject matter expertise in applying data science and machine learning to implement and run machine learning workloads on Azure.

Responsibilities for this role include designing and creating a suitable working environment for data science workloads; exploring data; training machine learning models; implementing pipelines; running jobs to prepare for production; and managing, deploying, and monitoring scalable machine learning solutions.

A candidate for this course should have knowledge and experience in data science by using Azure Machine Learning and MLflow.


Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

Skills measured

  • Design and prepare a machine-learning solution 
  • Explore data and train models 
  • Prepare a model for deployment 
  • Deploy and retrain a model