A graph is a data structure made of vertices (also called nodes) connected by edges. Unlike arrays, lists, or trees, graphs place no restriction on how items may connect: any vertex can link to any number of others, connections can be one-way or two-way, and cycles are allowed. That flexibility is exactly why graphs model so many real systems — road networks, social connections, web links, course prerequisites, and dependency chains in software.
In this course, graphs are the structure that ties together much of what you have already learned. Before you can implement adjacency lists or trace BFS and DFS, you need a precise vocabulary: vertex, edge, directed versus undirected, weighted versus unweighted, adjacency, degree, path, cycle, and connected versus disconnected. Getting these terms right early makes the later material about representation and traversal far easier to follow, because every algorithm description assumes them.
As you watch, focus on three things. First, how each video draws a graph and names its parts, so you can read a diagram quickly. Second, the difference an arrow makes — what changes when an edge is directed. Third, the terminology around moving through a graph (walks, paths, cycles), since traversal algorithms are formally described in those terms. Try sketching a small graph of your own, such as five friends and who follows whom, and label it using the vocabulary from each video.
This is the opening lecture of a graph data structure series, introducing what a graph is and why it matters as a data structure in programming. Based on its title and framing, it should define vertices and edges, show how graphs differ from other structures, and set up the topics that follow in the series. At 18 minutes it is the longest of the three, so expect a slower, example-driven pace.
CodeWithHarry is a widely watched programming channel, and this video's position as the first in a dedicated graph series makes it a natural starting point for the "What Is a Graph?", vertices, and edges subtopics.
A compact overview of graph fundamentals that, per its title, covers the basics plus the different types of graphs. Expect coverage of core terminology and the distinctions among graph varieties, most likely including directed versus undirected and weighted versus unweighted forms. Geekific provides an accompanying GitHub repository if you want to look at code alongside the explanation.
Its explicit focus on "types" maps directly onto the directed-versus-undirected subtopic, and its brisk 10-minute length makes it a good second pass or review after the longer introduction.
This tutorial focuses on the terms used to describe movement through a graph: walks, trails, paths, circuits, and cycles. The description confirms it begins by defining a walk as a sequence and then distinguishes the related terms from it. Expect worked examples on small graphs showing why one sequence counts as a path and another does not.
It sharpens the "Key Graph Vocabulary" subtopic with the precise distinctions that textbooks and algorithm descriptions rely on, which is useful groundwork before you study traversal.
These three videos build the vocabulary and mental models the module's outcomes depend on. The introductory videos establish vertices, edges, and the directed-versus-undirected distinction, which is the direct foundation for MO1 and for recognizing which graph type fits a given real-world relationship. Their coverage of graph types and structure also prepares you for MO2, since adjacency matrix and adjacency list trade-offs only make sense once you can reason about how many edges a graph has and whether edges are symmetric. The walks-and-paths tutorial supplies the exact terminology used when describing traversal order, supporting MO3 and MO5, and the shared vocabulary across all three carries into the implementation work in MO4.
These videos were chosen from YouTube on October 2, 2026. Each has captions; the player turns them on. Videos on YouTube can be changed or removed — if one no longer plays, tell your instructor. If a player does not appear, use its Watch on YouTube link.