Master Data Structures & Algo – Ace Leetcode & Blind 75+

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Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Duration & workload

4 weeks, 10 hours a week

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Overview

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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 provides a comprehensive understanding of data structures and algorithms, with a focus on solving Leetcode and Blind 75+ problems. You’ll develop essential skills for cracking technical interviews in top tech companies by learning efficient problem-solving and algorithmic techniques. The course begins with an introduction to resources, strategies, and time-saving tips to optimize your learning journey. You will tackle topics like arrays, strings, linked lists, binary trees, dynamic programming, and more, solving coding challenges along the way. You’ll learn key techniques such as hashing, sliding windows, two-pointers, and binary search through problems like "Two Sum," "Longest Substring Without Repeating Characters," and "Merge Intervals." The course also covers advanced topics like dynamic programming, graph traversal, and greedy algorithms. This specialization is ideal for learners preparing for technical interviews or those looking to strengthen their algorithmic skills. It’s designed for learners with basic programming knowledge, with an intermediate difficulty level. By the end of the specialization, you will be able to solve complex problems, optimize code, and confidently tackle technical interviews.

Syllabus

Course 1: Introduction to Fundamental Data Structures and Techniques
Course 2: Intermediate Algorithms: Graphs, Trees, and Backtracking
Course 3: Advanced Algorithms and Problem-Solving Techniques

Courses

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14 hours 48 minutes
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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 problem-solving skills with advanced techniques in dynamic programming, greedy algorithms, and bit manipulation. This course covers essential strategies like memoization and tabulation in dynamic programming to solve complex problems such as Fibonacci numbers, coin change, and palindromic substrings. You’ll also master greedy algorithms with problems like maximizing subarrays and minimizing the number of boats needed, enhancing your ability to approach optimization problems efficiently. Starting with dynamic programming, you will tackle various problems, from decoding strings to finding the longest increasing subsequence. As you advance, the course dives into greedy algorithms and the efficient merging of intervals to handle overlapping schedules or spaces. The course also explores matrix manipulations and bit-level operations, enabling you to solve problems related to bit counting, missing numbers, and binary representations. Perfect for those with a solid understanding of algorithms, this course prepares you to solve complex real-world challenges using advanced techniques. By the end, you’ll be equipped to tackle high-level problems that require both creative and optimized solutions. By the end of the course, you will be able to efficiently apply dynamic programming, greedy algorithms, bit manipulation, and matrix operations to solve advanced algorithmic challenges in both interviews and projects.
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14 hours 3 minutes
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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. Unlock the power of advanced algorithms with a focus on graphs, trees, and backtracking. Through this course, you will learn how to apply depth-first and breadth-first search techniques to solve problems in trees and graphs. From the basics of binary trees to complex graph traversals and backtracking algorithms, this course provides an in-depth exploration of key data structures and techniques used to solve real-world algorithmic challenges. The course kicks off with the essential concepts of binary trees, including traversal techniques like DFS and BFS. You'll work through problems like inverting a binary tree, calculating its maximum depth, and validating whether a binary tree is a binary search tree. As you progress, you’ll explore backtracking algorithms for solving problems such as the Combination Sum and Word Search, and dive into more advanced data structures like Tries to solve complex string-searching problems. Later in the course, you’ll tackle graphs and how to work with algorithms like Union-Find to determine connected components or verify the validity of a graph. You’ll also explore how to solve real-world problems such as Pacific Atlantic water flow, course schedules, and alien dictionaries through graph traversal techniques. This course is designed for learners with a basic understanding of data structures and algorithms who want to delve deeper into intermediate concepts. It’s perfect for anyone preparing for technical interviews or looking to expand their algorithmic problem-solving toolkit. By the end of the course, you will be able to solve complex graph and tree problems, apply backtracking techniques, and efficiently use advanced data structures like Tries and Heaps in real-world scenarios.
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16 hours 3 minutes
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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. Mastering data structures and algorithms is essential for excelling in technical interviews, and this course is your first step toward that goal. With detailed explanations and hands-on problem-solving, you’ll develop the skills to tackle common data structure challenges such as arrays, strings, linked lists, and more. As you progress, you’ll not only understand these concepts but also become proficient in applying them to real-world problems, all while learning optimized solutions and techniques. The course begins with an overview of the fundamental data structures, starting with arrays and strings, before delving into more complex topics like linked lists, stacks, and binary search. You'll solve problems like "Two Sum," "Group Anagrams," and "Valid Palindrome," learning how to approach them efficiently. Each section introduces essential algorithms and techniques such as two-pointer approaches, sliding windows, and fast & slow pointers, helping you build an in-depth understanding of these key concepts. Throughout the course, you'll engage with challenges that will prepare you for real interview scenarios. You'll explore essential strategies like hashing, sliding window, and binary search in problem-solving, equipping you with a strong foundation for tackling technical interviews. The course concludes with a focus on optimizing solutions and improving time complexity. This course is perfect for aspiring software engineers, developers, or anyone looking to strengthen their understanding of data structures and algorithms. A basic understanding of programming and problem-solving is recommended, but no prior expertise is required. The course is designed to be accessible to learners at the beginner to intermediate level. By the end of the course, you will be able to confidently solve data structure problems, optimize your code, and apply your knowledge to real-world coding challenges in interviews and projects.