Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Through this course, you’ll gain a deeper understanding of advanced data structures and problem-solving techniques. You'll explore core data structures such as queues, heaps, binary search trees, and binary trees, learning how to implement and optimize them. By working through a variety of real-world coding problems, you’ll also hone your algorithmic thinking skills and ability to tackle complex coding challenges. The course is designed to walk you through the fundamentals and more advanced concepts, starting with the implementation of basic structures like queues and progressing to more intricate topics like binary search trees, heaps, and sliding window methods. You'll work with different data structures in various programming languages, including JavaScript, to optimize solutions and improve performance. As you proceed, you will also tackle problem-solving strategies using methods like sliding window, two-pointer, binary search, and dynamic programming, with ample practice problems to reinforce each technique. This course is perfect for intermediate learners familiar with basic programming concepts and data structures. If you’re looking to improve your algorithmic skills, or if you’re preparing for coding interviews, this course is the perfect way to take your understanding to the next level. By the end of the course, you will be able to implement advanced data structures, solve real-world algorithmic problems, optimize code for efficiency, and prepare for technical interviews.

Syllabus

Queue

In this module, we will explore the fundamentals of queues as a data structure. You will learn to implement queues using both linked lists and arrays, ensuring efficient operations. By the end of this section, you will be comfortable with practical queue implementations in JavaScript.

Sliding Window Method

In this module, we will dive into the sliding window method, a powerful technique for optimizing algorithms. You'll apply this technique to efficiently solve problems like the "Longest Substring Without Repeating Characters" and "Sliding Window Maximum."

Two Pointer Method

In this module, we will focus on the two-pointer technique. You'll learn to apply it in solving problems like "Trapping Rain Water" and "Container with Most Water." This method will also help you check for palindromes efficiently.

Binary Search

In this module, we will introduce you to binary search, a highly efficient algorithm for searching sorted arrays. You’ll gain hands-on experience in implementing it and solving real-world problems such as "Search Insert Position" and "Magnetic Force Between Two Balls."

Binary Trees

In this module, we will introduce you to binary trees, focusing on core concepts like tree traversal and key operations. You’ll tackle problems such as "Maximum Depth of a Binary Tree" and "Invert Binary Tree" while gaining a deeper understanding of tree structures.

Heaps

In this module, we will explore heaps, a tree-based structure used for priority queues. You will learn heap operations such as insertion and deletion, and solve problems like finding the "Kth Largest Element in an Array."

Binary Search Tree

In this module, we will explore Binary Search Trees (BSTs), a tree-based data structure that ensures efficient searching, insertion, and deletion. You will also solve various problems, such as "Validate Binary Search Tree" and "Lowest Common Ancestor of a BST."