LEETCODE In C++ - Top 100 Coding Interview Problems

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Coursera Specialization
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English
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Certificate Available
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Self-Paced
Level

Intermediate

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This specialization 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 specialization. This specialization helps you prepare for coding interviews by solving top LeetCode problems using C++. You will strengthen problem-solving skills, develop algorithmic thinking, and build confidence in analyzing time and space complexity to approach interviews with clarity and precision. You will start with fundamentals like Big O notation and complexity analysis to understand performance trade-offs. The specialization then covers essential data structures such as arrays, linked lists, stacks, and hash tables, reinforced through practical interview-style problems. As you advance, you will explore techniques like sliding window, two pointers, recursion, backtracking, and binary search. You will also work with trees, heaps, dynamic programming, and graphs to solve more complex challenges efficiently. Designed for aspiring software engineers, students, and professionals, this intermediate-level specialization requires basic C++ knowledge. By the end, you will be able to analyze algorithms, apply optimized solutions, and confidently tackle technical coding interviews.

Syllabus

Course 1: Introduction to Data Structures and Algorithmic Foundations
Course 2: Advanced Problem-Solving Methods and Search Algorithms
Course 3: Advanced Data Structures and Algorithm Optimization

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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. Elevate your algorithmic expertise by mastering advanced data structures and optimization techniques used in high-level problem solving. This course focuses on recursion, trees, heaps, dynamic programming, and graph algorithms, enabling you to design efficient and scalable solutions for complex computational challenges. You will begin with recursion and backtracking, learning how to systematically explore solution spaces through problems like subsets, combination sum, and N-Queens. The course then transitions into binary trees and binary search trees, covering traversal techniques, structural properties, and real-world problem-solving patterns. As you progress, you will explore heaps for priority-based operations and dive deep into dynamic programming to optimize overlapping subproblems. You will also gain insights into greedy strategies, bit manipulation techniques, and graph algorithms, solving problems such as course scheduling and network delay time. This course is designed for learners with a solid foundation in basic data structures and algorithms who want to advance their problem-solving capabilities. It is best suited for intermediate to advanced learners preparing for technical interviews or competitive programming. By the end of the course, you will be able to design optimized algorithms using advanced data structures, apply dynamic programming and graph techniques, and confidently solve complex, real-world coding challenges.
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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.
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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. Build a strong foundation in data structures and algorithms to confidently tackle coding interviews and real-world problem solving. You will learn how to analyze time and space complexity, apply Big O notation, and understand how efficient code impacts performance. Through hands-on practice, you will strengthen your logical thinking and develop a problem-solving mindset essential for technical roles. The course begins with an introduction to coding interview preparation using Leetcode, guiding you on how to approach problems strategically. It then dives deep into time and space complexity, covering both theoretical concepts and practical examples, including recursive cases and live demonstrations to reinforce your understanding. As you progress, you will explore core data structures such as arrays, linked lists, and hash tables, learning their strengths, limitations, and real-world applications. Each section is paired with carefully selected problems, including popular interview questions like Two Sum, Maximum Subarray, and Linked List Cycle, enabling you to apply concepts effectively. This course is ideal for aspiring software engineers, students, and professionals preparing for coding interviews. Basic programming knowledge is recommended, and the course is designed at a beginner to intermediate level for gradual skill development. By the end of the course, you will be able to analyze algorithm efficiency, solve complex coding problems using key data structures, and confidently approach technical interviews with optimized solutions.