Data structures and algorithms are crucial for efficient problem-solving in computer science, enabling effective data organization and manipulation for fast, reliable software. Learning them enhances your coding skills and prepares you for technical interviews and real-world challenges. This article lists the top data structure and algorithms courses to help you excel in software development and interviews.
Foundations of Data Structures and Algorithms Specialization
This course covers the fundamentals of data structures and algorithms with a focus on data science applications. It covers topics including arrays, hash-tables, heaps, trees, graphs, and various others.
Data Structures and Algorithms Specialization
This course teaches algorithms and data structures through hands-on coding challenges and real-world applications. It covers topics like greedy algorithms, binary search, and dynamic programming and includes nearly 100 programming problems to solve.
Algorithms, Part I
This course provides essential knowledge on algorithms and data structures, emphasizing Java implementations and performance analysis. This course is divided into two parts, the first one covering basic data structures, sorting, and searching.
Algorithms, Part II
This course continues from the previous one, offering fundamental knowledge of algorithms and data structures, with a primary focus on graph and string algorithms. Students willing to dive deeper into the topic can refer to the book ‘Algorithms,’ upon which the course is based.
Algorithms and Data Structures Tutorial – Full Course for Beginners
This course covers algorithms and data structures, focusing on their fundamental concepts, measurement, and evaluation. It includes three main parts: algorithms, data structures, and an in-depth look at sorting and searching algorithms, teaching how they are used to solve problems.
Algorithms Specialization
This specialization introduces algorithms with a focus on conceptual understanding for those with some programming experience. It covers topics like divide and conquer, graph search, shortest paths, greedy algorithms, and NP-complete problems, preparing learners for technical interviews and advanced discussions in computer science.
Data Structures & Algorithms Using C++
This self-paced course teaches how to implement data structures and algorithms in C++, focusing on efficiency and real-world problem-solving. The course teaches about pointers, dynamic storage, recursion, sorting, and more, helping learners gain the ability to analyze and measure program efficiency.
Foundations of Data Structures
This course covers essential data structures for efficient algorithm design, starting with basic data types and progressing to sequences, trees, sets, maps, and graphs. This course is part of a Computer Science program that includes programming basics, object-oriented programming, and algorithms.
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues
The Data Structures & Algorithms course reviews key Java techniques and introduces time complexity. It covers arrays, linked lists, and their use in implementing ADTs like stacks, queues, and deques, emphasizing recursion and amortized analysis.
Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps
This course is an extension of the previous course and covers nonlinear and hierarchical data structures like trees, Binary Search Trees (BSTs), Binary Heaps, HashMaps, and SkipLists. It emphasizes time complexity, with a focus on tree properties, BST operations, heap access, and collision strategies in HashMaps.
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