Textbook in PDF format Data and information visualization has become the single most vital skill for understanding big data and driving effective decision-making. The amount and complexity of information produced in science, engineering, business, and everyday human activity are increasing at staggering rates and visualization helps people understand and analyze information. This textbook offers a complete overview of visualization techniques in sequential form to visualize the different types of data, like tables, graphs, trees, and text. We will explore how visualization goes beyond presenting information by leveraging the power of computer interaction to help people analyze, understand, and make decisions from data. Moreover, we will describe some fundamental principles of creating aesthetic visualization. The final section on implementation includes a practical guide to the best tools and libraries (like D3.js) and the design principles for creating compelling dashboards, concluding with the emerging intersection of AI and visualization and visual analytics for deep learning. By the end of this book, you will transition from a data novice to a visualization expert, capable of applying advanced network and multidimensional techniques. You will be fully equipped to handle any data structure and leverage AI for better insights, giving you a competitive edge in data science and visual analytics roles. Artificial Intelligence (AI) techniques like machine learning (ML) have made tremendous advancements in recent times and are successfully utilized for many tasks like code generation and question answering. There is also a lot of interest in applying AI techniques to assist in visualization. Like common data formats like text and images, visualizations are increasingly created and analyzed using the power of AI. In this chapter, we will discuss the AI techniques for visualization tasks such as generating and understanding visualizations. Who this book is for The book is for anyone who wants to gain insights from data using visualization techniques - students, academicians, data scientists, software developers, etc. A basic knowledge of software is all that is required to gain insights from the book. Contents Introduction Data Visual Encoding Visualizing Tables Visualizing Multi-dimensional Data Interactions Visualizing Time Visualizing Trees Visualizing Graphs Graph Tree Interactions Visualizing Text Implementation Design Principles Visual Analytics for Deep Learning AI Techniques for Visualization