Getting usable information from the vast amount of data we are immersed into requires a combination of methodologies, tools, techniques, algorithms and ingenuity. Creating views, extracting trends, defining patterns, identifying clusters are all elements we need to manage large data. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This course will examine methods that have emerged from both fields and proven to be of value in recognizing patterns and making predictions from an applications perspective. Final goal of the course is to provide the students with a “data toolbox” they can use in their activities. This “toolbox” contains methods and tools that students will use themselves during the course for real world applications. The course is hand-on, but no coding is required, using Open Source Data Science tools that are based on Graphical User Interfaces.