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Workshop: Moving from BI to AI: Artificial Intelligence Skills for Business Intelligence Professionals
Are you interested in reusing your existing BI skillset in order to add Artificial Intelligence to your skillset? Is your organisation interested in applying AI at a practical level? If so, this precon is for you.
In this precon, you will leverage your existing BI skillset to learn Microsoft’s latest AI technologies. You will learn AzureML, using your existing SSIS expertise. You will also learn R and Python, using your knowledge of SQL in SQL Server to get a working knowledge of these languages and their use in AI. You will use your conceptual knowledge of Business Intelligence to learn how to choose the right model for your AI work, and how to identify its value and validity.
Join this session to add AI to your organization’s technical capability, springboarding from skills that you already possess.
Moving from BI to AI: Artificial Intelligence skills for Business Intelligence professionals
9.00am AI for the Enterprise
AI for the Enterprise
What is AI? Terminology that you need to know
Blueprint for AI in the Enterprise
Technology Overview; how do you choose the best tools to provide business value?
In this section, we will look at what you need to know to set the scene for AI for the enterprise. There is a very wide range of technologies in the AI space, and this section will introduce the key players and how they compare with one another, along with clear explanations on how they are used best. The session will also propose a blueprint for delivering successful AI projects, from the business perspective.
10.00am Get started with AI in Azure
- Introduction to AzureML
- Build simple machine learning models with Azure Machine Learning
In this section, you will get hands-on experience in practice building a machine learning model from end-to-end, using AzureML. This is intended to formalize some of the knowledge you have learned so far. In this section, you will ingest data, select a model, train and test a model, and make it production-ready. Then, you can visualize your results in Power BI.
11.30 Selecting your model in AI
An exploration of models in AI
Selecting models in AI
Evaluating models in AI
In this section, we will cover AI models in detail. We will look at the models themselves, their differences and similarities, and how to choose between the models. We will also look at ways of evaluating models.
12.30 – 1.30 Lunch
1.30 Working with Microsoft ML Server and R
- Fundamentals of R
- Microsoft ML Server
- Using R with Microsoft ML Server
In this section, we will cover the fundamentals of R, and how we can use it to create robust, production models using Microsoft ML Server. R is a first class citizen in Microsoft’s Data Platform offerings, and it touches other technologies, such as AzureML, SQL Server and Power BI. We will cover its use in Microsoft Machine Learning Server to help provision a flexible enterprise platform for analyzing data at scale, building intelligent apps, and discovering valuable insights across your business. Machine Learning Server meets the needs of all constituents of the process – from data engineers and data scientists to line-of-business programmers and IT professionals. It offers a choice of languages and features algorithmic innovation that brings the best of open-source and proprietary worlds together.
3.00 Python Data Science Notebook and Labs
Python is an important skill in analysing data, data science and artificial intelligence. In the final segment, you will learn about Python, how to use it, and how to use Notebooks to work with your code.
5.00 Wrap up and QA