Practical Machine Learning, AI and Data Science on SQL Server 2017, Microsoft ML Server, R, and Azure ML - with Rafal Lukawiecki

This live classroom course is new for 2018! It focuses on the newest technologies of Microsoft Machine Learning Server and SQL Server 2017. By popular demand, Part 2 of this course teaches programming in R, however most of the course is also applicable to Python programmers, as the key libraries are the same.

You start with the 2-day Introduction course which introduces the most important concepts and Tools: 
Introduction to Machine Learning, AI & Data Science with Azure ML 

Then you continue with the 3-day Intermediate course that teaches you R and how to use it for machine learning on the Microsoft platform: 
Intermediate Machine Learning in R on SQL Server and Microsoft ML Server

Audience:

If you have attended a prior course on Machine Learning, like Rafals week-long class Practical Data Science that was offered in 2015–2017, and if you are versed in model validity, accuracy, and reliability - you shold consider attending the 3-day Intermediate course only. 

Ask yourself these questions:

  • Can I explain the difference between cross-validation and hold-out testing?
  • Do I know which business metrics correspond to precision and which to recall?
  • Is model accuracy more important than reliability, and how does a boosted decision tree work?

If in doubt, please attend both the Introduction course and the Intermediate course. 

Prerequisites:

There are no formal prerequisites to attend this course because everyone will benefit from the lectures and the discussions. However, it will be useful with some knowledge of linear algebra, statistics and probabilty and/ or programming. 

Format:

The course format is 50% lectures, 30% demos and 20% tutorials. 
You are encouraged to follow the demos on your machine, and you will be challenged to find answers to 3 larger problems during the tutorials. While they are a hands-on part of the course, if you prefer not to practice, you are welcome to use that time for additional Q&A, or to analyse your own data. We will provide you with all the necessary data sets, and we will explain what free or evaluation edition software needs to be installed to follow the course on your own laptop. In some training centres we are able to provide pre-built machines which you can use instead of your own—please enquire. You will need an Azure account (even a free one) during the course. You can copy course experiments and data into your workspace for learning and for future reference after the course. 

About Rafal Lukawiecki

As Data Scientist at Project Botticelli Ltd, Rafal focuses on making advanced analytics and artificial intelligence easy and useful for his clients.

He can help you find valuable, meaningful patterns and statistically valid correlations using data mining and machine learning in data sets both big and small. Rafal is also known for his work in business intelligence, data protection, enterprise architecture, and solution delivery. While majority of his clients come from consumer and corporate finance, entertainment, healthcare, IT, retail, and the public sectors, Rafal has worked in almost all industries.

He has been a popular speaker at major IT conferences since 1998.

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