Description
Come learn the fundamentals of analysis & machine learning in R, and how to operationalise your work.
In this live two-day course, we’ll take you from no data science knowledge to understanding the fundamentals and being able to put them into production using SQL Server.
Focussing on using R, you’ll learn how to important exploratory data analysis, build common predictive models, and embed them with best practices.
You won’t be a PhD in Machine Learning by the end of this, but you’ll be comfortable coding in R and understand the basics of data science.
Agenda/modules:
- Basics of R – Understand how R fits into the data science world, get comfortable with the coding environment, and perform basic manipulations of key R objects.
- Data Manipulation in R – Learn how to read data in from different sources, work with columns and rows, join tables, and more. This is the biggest task in any data science project so we need to do this well.
- Data Visualization in R – Get practiced with exploring and presenting data in static and interactive graphics to help you and others gain understanding.
- Machine Learning Fundamentals – Understand the most common types of models, what they’re used for, and how to code them in R. Work through the data science process, from data preparation to sampling to building models to evaluating them.
- Working with R from SQL Server – Understand how you can work with R in SQL Server and what architectural and operational considerations you should think about. Embed models into SQL Server and learn how to use these models for batch and real-time predictions.
About the instructor: Steph Locke is a Microsoft Data Platform MVP with a decade of business intelligence and data science experience. Having worked in a variety of industries (including finance, utilities, insurance, and cyber-security,) Steph has tackled a wide range of business challenges with data. She has a broad background in the Microsoft Data Platform and Azure. She’s equally conversant with open source tools; from databases like MySQL and PostgreSQL, to analytical languages like R and Python.
This is a live online class. We host it in GoToWebinar, live with Steph Locke on webcam, with a 75-minute lunch break. Audio can come through either your computer audio, or by dialing into a US phone number – headset recommended either way. For more information, check out the Training Logistics PDF for our online classes.
Online class times:
- October 10-11, 13:00 UTC (9AM New York City)
Because this is a brand new class, it doesn’t include Instant Replay capability.
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