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. Take your algorithmic thinking to the next level by mastering advanced problem-solving techniques used in top technical interviews. This course equips you with efficient strategies like stacks, sliding window, two pointers, and binary search, enabling you to solve complex problems with optimized approaches and improved performance. You will begin by exploring stacks and their practical applications in solving problems such as valid parentheses, reverse polish notation, and next greater elements. From there, the course transitions into the sliding window technique, helping you tackle substring and window-based optimization problems with clarity and efficiency. As you progress, you will dive into the two-pointer method and interval-based problem solving, followed by mathematical and geometric challenges like spiral matrices. The course culminates with an in-depth understanding of binary search, including advanced applications such as searching in rotated arrays and optimizing search over ranges. This course is ideal for learners with prior knowledge of basic data structures and algorithms who want to strengthen their problem-solving skills. It is best suited for intermediate learners preparing for coding interviews or aiming to improve algorithmic efficiency. By the end of the course, you will be able to apply advanced problem-solving patterns, optimize search strategies, and confidently solve complex algorithmic challenges across a wide range of scenarios.

Syllabus

Stacks

In this module, we will explore the stack data structure, diving into its applications in solving common algorithmic problems. You'll learn to use stacks for problems like valid parentheses and evaluate expressions in Reverse Polish Notation, equipping you with practical problem-solving skills.

Sliding Window Method + Practice Problems

In this module, we will focus on the sliding window technique, a powerful approach for solving array-related problems efficiently. You’ll gain hands-on experience with problems like finding the longest substring without repeating characters and maximizing window values.

Two Pointer Method

In this module, we will dive into the two-pointer technique, covering its application to problems like validating palindromes and solving geometric challenges like trapping rainwater. By mastering this method, you’ll tackle complex problems more efficiently.

Math & Geometry

In this module, we will explore mathematical and geometric problem-solving techniques. You’ll learn to print a matrix in spiral order and solve similar complex geometric challenges, combining both math and algorithmic thinking.

Intervals

In this module, we will focus on problems involving intervals, such as merging overlapping ranges and finding insert positions in sorted arrays. These interval-related problems will sharpen your ability to handle range-based challenges efficiently.

Binary Search Theory & Binary Search Over Rotated Sorted Arrays

In this module, we will introduce binary search, one of the most efficient searching algorithms. You'll learn how to apply binary search to both standard and rotated sorted arrays, solving problems like finding the first and last positions of an element and the minimum value in a rotated array.

Binary Search Over Range

In this module, we will apply binary search to problems that involve searching over a range, such as determining the minimum eating speed for Koko and calculating the magnetic force between balls. You'll enhance your binary search skills to solve these range-based challenges efficiently.