A binary tree is a hierarchical data structure built from nodes connected by edges, where every node has at most two children, conventionally called the left child and the right child. Unlike arrays and linked lists, which arrange data in a single line, trees branch — and that branching is what makes them so useful for organizing data that will later be searched, sorted, or traversed. Before you can insert into or search a binary search tree, you need fluency with the vocabulary: node, edge, root, leaf, parent, child, sibling, subtree, depth, and height.
This topic is the foundation for everything else in the module. The root node is the single entry point with no parent; leaf nodes are the endpoints with no children; every other node sits in a parent-child relationship that defines the shape of the structure. The "binary constraint" — at most two children per node — is the structural rule that separates binary trees from general trees, and it is what makes traversal and search algorithms predictable enough to analyze.
As you watch, focus on the terminology and on the pictures. Try to redraw each example tree yourself and label the root, the leaves, and the edges. Ask yourself for every diagram: how many children does each node have, which nodes are parents of which, and would this structure still qualify as a binary tree if one more child were added? Pay attention also to how speakers distinguish a general binary tree from the more constrained variants (full, complete, perfect, and binary search trees) that come later in the module.
A beginner-friendly introduction to the tree data structure in general, covering what a tree is and walking through the core terminology — root, children, siblings, and related terms — with diagrams. It establishes nodes and edges as the building blocks of any tree before narrowing toward more specific tree types. Expect a slower, example-driven pace with hand-drawn illustrations.
CodeWithHarry is a widely followed programming channel with a strong track record for clear beginner explanations, and this video directly covers the Nodes and Edges, Root Node, Leaf Nodes, and Parent-Child Relationships subtopics in one place.
A concise lecture-style treatment of binary trees specifically, presenting the formal definitions and terminology that underpin binary search trees. Because it is framed as a prerequisite to BSTs, it is likely to emphasize the structural rule that each node has at most two children and to name the left and right subtrees precisely. Slides accompany the presentation.
Delivered by a university instructor in a course context much like this one, it targets the Binary Constraint subtopic head-on and gives you the precise definitions you will need when the module moves to BST ordering.
A classroom lecture segment on binary trees from a university CS course, presented as the lead-in to binary search trees in the following class. It discusses the binary tree structure itself and why that structure is useful, positioning it as the basis for search-oriented variants. The format is an in-class explanation rather than a polished production.
It offers a second academic perspective at a similar level to this course and explicitly bridges from the general binary tree structure to binary search trees, reinforcing the distinction you are expected to make in MO1.
Together these three videos build the vocabulary and structural intuition required by MO1: identifying nodes, edges, the root, leaves, and parent-child relationships, and recognizing the at-most-two-children rule that defines a binary tree. CodeWithHarry supplies the broad tree terminology, while the Wortman and cs128 lectures narrow that terminology to binary trees and point forward to the ordering property that distinguishes a BST. Although traversal (MO2), insertion and deletion (MO3), complexity analysis (MO4), and JavaScript implementation (MO5) are addressed in later topics, none of that work is possible without the structural foundation and shared vocabulary these videos establish here.
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.