Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.
After completing this course, students will be able to:
Design and prepare a machine learning solution
Explore data and train models
Prepare a model for deployment
Deploy and retrain a model
Lumify Work has been delivering effective training across all Microsoft products for over 30 years. We are proud to be both Australia's and New Zealand’s first Microsoft Gold Learning Solutions Partner and the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers (MCTs) in ANZ. All Lumify Work Microsoft Azure courses follow Microsoft Official Curriculum (MOC) and are led by MCTs.
This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
Successful Azure Data Scientists start this role with a fundamental knowledge of cloud computing concepts, and experience in general data science and machine learning tools and techniques.
Specifically:
Creating cloud resources in Microsoft Azure.
Using Python to explore and visualize data.
Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.
If you are completely new to data science and machine learning, please complete Microsoft Azure AI Fundamentals first.
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
