Getting started with Data Science in Azure is often quite daunting. There are a huge variety of different options to select and knowing which one to use and when depends a lot on your current skills and what you are trying to achieve. Then there is the added complication that the tools we are using are constantly evolving and improving. It is understandable that getting started is difficult.

In this full day session we will explore everything you need to know to get started with Machine Learning in Azure. We will start the day getting you up to speed with Machine Learning. We will explore the Machine Learning flow and get to know the data we will be working with. From there we will five in to Azure Machine Learning Services. We will spend most of our time here, looking in to working with data, mounting data and creating datasets and diving deep on Azure Machine Learning's workspace.

We will then define the term "Citizen Data Scientist" and build a series of models together, initially in AutoML and then using the Machine Learning designer (a GUI interface for building models). Which should you use and when? We will look at which is best under which circumstances and how to get the best out of each type.

Once we have mastered the skills of the "Citizen data scientist" we will look at how an experienced Data Scientist develops models. We will initially look at compute backed notebooks in Azure ML before moving on to look at how to build models at scale in Azure Databricks. Throughout the day we will also look at scenarios for tracking with either the tracking services in Azure ML or MLFlow in Databricks.

Join Terry McCann, Director of AI and Microsoft MVP for AI as we tackle a day full of demos and labs looking at everything you need to know to get started with Machine Learning in Azure