Using Azure Machine Learning’s MLOps capabilities, students will gain experience in understanding ML models, protecting people and their data, and controlling the end-to-end ML lifecycle at scale.
Overview
Syllabus
- Welcome to Machine Learning Engineer with Microsoft Azure
- Welcome to Udacity! We're excited to share more about your nanodegree and start this journey with you!
In this course, you will learn more about the pre-requisites, structure of the program, and getting started! - Using Azure Machine Learning
- Machine learning is a critical business operation for many organizations. Learn how to configure machine learning pipelines in Azure, identify use cases for Automated Machine Learning, and use the Azure ML SDK to design, create, and manage machine learning pipelines in Azure.
- Machine Learning Operations
- This course covers a lot of the key concepts of operationalizing Machine Learning, from selecting the appropriate targets for deploying models, to enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines. All these concepts are part of core DevOps pillars that will allow you to demonstrate solid skills for shipping machine learning models into production.
- Capstone - Azure Machine Learning Engineer
- This capstone project gives you the opportunity to use the Azure Machine learning knowledge you have obtained from this Nanodegree to solve the problem of your interest.
- Career Services
- The Careers team at Udacity is here to help you move forward in your career - whether it's finding a new job, exploring a new career path, or applying new skills to your current job.
Taught by
Noah Gift, Alfredo Deza, Erick Galinkin and Soham Chatterjee
