This chapter explores the intersection of complex network theory and time series analysis, introducing methods for representing and analyzing time-dependent data using network-based approaches. The chapter begins with the basics of complex network theory, covering fundamental concepts such as the theoretical definition of a graph, which forms the basis for network-based analysis. Next, it discusses topological network measures, which help characterize the structure and dynamics of complex networks. These include: The chapter then examines different types of networks, focusing on: A major section is dedicated to methods for converting time series into complex networks, including: Finally, the chapter provides extended examples demonstrating the transformation of time series data into networks and analyzing them using network measures. Case studies include: By the end of this chapter, readers will understand how to model time series as complex networks, extract meaningful structural insights, and apply network theory to real-world and simulated data.