This course provides an introduction to data visualization and representation with essential concepts and methods. The objective of the course is to teach students methods and tools for gaining insight into data and drawing conclusions for analytical reasoning and decision making. The course starts off by giving real-world examples and abstracting from these examples leads towards a taxonomy for data types, their characteristics, and relations. The course comprises methods for visual analytics of various kinds of data including relational, structured (tree, graph, and networks), semi-structured and unstructured data (text or document), high-dimensional, spatial-temporal. The course also trains the students with methods used for visual data representations (such as visual grammars), visual encoding, and interaction mechanisms, leading tointeractive visual analytics. Some other components such as data transformation, aggregation, classification, clustering, and outlier detection are an integral part of the visual analytics process.