## Learning Outcomes

Attendees of this course learn to program with R from the scratch. Basic R code is introduced using the free R engine and RStudio IDE. A lifecycle of a data science project is explained in details. The attendees learn how to perform the data overview and do the most tedious task in a project, the data preparation task. After data overview and preparation, the analytical part begins with intermediate statistics in order to analyze associations between pairs of variables. Then the course introduces more advanced methods for researching linear dependencies.

Too many variables in a model can make its own problem. The course shows how to do feature selection, starting with the basics of matrix calculations. Then the course switches more advanced data mining and machine learning analyses, including supervised and unsupervised learning. The course also introduces the currently modern topics, including forecasting, text mining, and reinforcement learning.

Finally, the attendees also learn how to use the R code in SQL Server, Azure ML, and Power BI through labs, and how to use Python for inside all of the tools mentioned through demos.