Colleagues, the Machine Learning Engineer for Microsoft Azure training program will strengthen your machine learning skills and build practical experience by training, validating, and evaluating models using Azure Machine Learning. Learn by building and deploying sophisticated machine learning solutions using popular open source tools and frameworks, and gaining practical experience running complex machine learning tasks using the built-in Azure labs accessible inside the Udacity classroom. According to Indeed.com average base salaries for Machine Learning Engineers is $131,099. Prior experience with Python, Machine Learning, and Statistics is recommended. Skill-based training modules - each with hands-on labs - include: 1) Using Azure Machine Learning - learn 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 (Project: Optimizing and ML Pipeline in Azure); 2) Machine Learning Operations - 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 (Project: Operationalizing Machine Learning); and 3) Capstone Project - use Azure’s Automated ML and HyperDrive to solve a task. Finally, you will have to deploy the model as a web service and test the model endpoint (Project: Training and Building a Machine Learning model in Microsoft Azure).
Enroll today (eams & execs welcome): https://tinyurl.com/2p98sk7a
Much career success, Lawrence E. Wilson - Artificial Intelligence Academy