Gain a comprehensive understanding of network analysis with our course, Introduction to Networks. This course will provide you with a solid foundation in the fundamental concepts of network analysis. Starting with an overview of social networks, vertices, and edges, you will learn how to effectively explore and visualize network data using the igraph R package. As you progress through the course, you will delve deeper into the analysis of directed networks. You will learn how to identify key relationships between vertices and apply your newfound skills to analyze a network data set focused on measles transmission in Hagelloch. In addition to understanding network structures and graphs, you will also learn how to characterize network substructures by examining network density and average path length. The course will guide you through the concepts of randomization and random graphs, as well as triangles, transitivity, and visualizing cliques. Furthermore, you will discover how to identify relationships using assortativity in igraph. Assortativity allows you to determine the likelihood of two vertices being connected if they share a common attribute, whether it be numerical or categorical. By utilizing the ASSORTATIVITY function within igraph, you will explore the impact of gender on a friendship network dataset and validate your findings through randomizations. To enhance your network visualization skills, the course will introduce you to threejs, a powerful R package. You will learn how to create interactive network plots using threejs, expanding your visualization capabilities beyond igraph. Additionally, you will explore advanced techniques to further develop your visualizations. By the end of this course, you will have gained a comprehensive understanding of network analysis, enabling you to effectively explore, analyze, and visualize network data using the igraph R package and threejs.