AI Bootcamp for Professional AI Developers

In preparation for the upcoming Machine Learning Boot Camp, there are a few things you need to do to be able to take the class. These activities take about 2.5 hours in total, and must be completed prior to showing up for the event. Failure to do so will put you begind the rest of the class and divert your time and attention from the material covered throughout the bootcamp. As proof you have completed the steps below, you must bring the “Web Service ID” code (described below) with you to sign-in at the event.

What you will need:

– Use a code-repository system with the Azure Machine Learning Workbench using the TDSP structure.
– Create an example environment.
– Use the TDSP and AMLS for data acquisition and understanding.
– Use the TDSP and AMLS for creating an experiment with a model and evaluation of models.
– Use the TDSP and AMLS for deployment.
– Use the TDSP and AMLS for project close-out and customer acceptance.
– Execute Data preparation workflows and train your models on remote Data Science Virtual Machines (with or without GPUs) and HDInsight Clusters running Spark.
– Manage and compare models with Azure Machine Learning.
– Explore hyper-parameters on Spark using Azure Machine Learning.
– Leverage Batch AI training for parallel training on GPUs.
– Deploy and Consume a scoring service on Azure Container Service.
– Collect and Analyze data from a scoring service in production to progress the data science lifecycle.

Content sourced by Microsoft.