
Learn binary tree concepts with a beginner-friendly Python crash course on data structures and algorithms, using animated explanations and code walkthroughs to prepare you for interview-style problems.
Learn how binary trees organize data with nodes, a single root, leaves, and at most two children; identify key criteria and model trees with left and right pointers.
Define a Python binary tree node class with an initialize method, storing a value and left and right pointers defaulting to None, then wire a sample tree for testing algorithms.
Explore depth first traversal on a binary tree using a stack. Learn the depth first values problem, root handling, push and pop operations, and O(n) time and space complexity.
Code along with us at https://structy.net/problems/depth-first-values
Master breadth-first traversal on a binary tree by using a queue to visit nodes level by level from the root, visiting B and C before D, E, and F.
Code along with us at https://structy.net/problems/breadth-first-values
Compute the total sum of all node values in a binary tree with a recursive depth-first approach, treating null nodes as zero, as shown with a final result of 25.
Code along with us at https://structy.net/problems/tree-sum
Explore more data structure and algorithm topics with struct.net, designed for beginner-friendly learning and interview prep. Animations reveal the solution thought process, with language-specific Python, JavaScript, Java, and C++ walkthroughs.
Code along with us at https://structy.net/problems/tree-includes
Explore solving binary tree minimum value problem with depth-first recursion, returning infinity for nulls and combining left, right, and node values to find the minimum in O(n) time and space.
Code along with us at https://structy.net/problems/tree-min-value
Learn to compute the maximum root-to-leaf path sum in a binary tree using recursion. Treat leaves as base cases, handle null children with negative infinity, and combine results.
Code along with us at https://structy.net/problems/max-root-to-leaf-path-sum
Conclude our binary tree algorithms crash course by guiding practice on binary trees and essential concepts for technical interviews, with beginner-friendly explanations and Structs.net resources.
Welcome to the Binary Tree Algorithms Crash Course in Python. This mini-course is designed to give you the background and tools you need to start solving Binary Tree interview problems. We'll give you all the essential knowledge you need in less than three hours. This course is designed especially for beginners, so you don't need to know any data structures and algorithms to get started.
This crash course is a great fit for you if:
you are a beginner to data structures and algorithms
you need a structured system to learn about binary trees in a short amount of time
you don't like wasting your time drilling random, disconnected leetcode problems
you want to build a robust visual and mental understanding of algorithms
you want to be taught by a former Google engineer with years of professional teaching experience
The course features video explanations for every piece of curriculum. This includes conceptual video animations and Python implementation walkthroughs for every problem. We will start simple and progress to more complex problems to ensure that you understand every step of the way.
During the course we'll learn how to:
master the two essential algorithms that serve as the backbone to virtually every Binary Tree problem
apply these algorithms to solve common technical interview problems
visualize the thought-process behind each problem
analyze the Big-O time and space complexity of solutions
This course is the most efficient way to learn about Binary Tree algorithms.