Data structures and algorithms are crucial to efficient problem solving in computing, enabling effective data organization and manipulation for fast and reliable software. Learning them improves your coding skills and prepares you for technical interviews and real-world challenges. This article lists the best algorithms and data structure courses to help you excel in software development and interviews.
Specialization in Fundamentals of Data Structures and Algorithms
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 several others.
Specialization in Data Structures and Algorithms
This course teaches algorithms and data structures through practical coding challenges and real-world applications. It covers topics such as greedy algorithms, binary search, and dynamic programming and includes almost 100 programming problems to solve.
Algorithms, Part I
This course provides essential knowledge of algorithms and data structures, with an emphasis on Java implementations and performance analysis. This course is divided into two parts, the first covers basic data structures, sorting and searching.
Algorithms, Part II
This course is a continuation of the previous one and offers fundamental knowledge of algorithms and data structures, with a primary focus on graph and string algorithms. Students who wish to delve deeper into the topic can consult the book 'amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X”>Algorithms,' on which the course is based.
Algorithms and Data Structures Tutorial: Complete 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 search algorithms, teaching how they are used to solve problems.
Specialization in Algorithms
This specialization introduces algorithms with a focus on conceptual understanding for those with some programming experience. It covers topics such as divide and conquer, graph search, shortest paths, greedy algorithms, and NP-complete problems, preparing students for technical interviews and advanced discussions in computer science.
Data structures and algorithms using C++
This self-paced course teaches how to implement data structures and algorithms in C++, focusing on efficiency and solving real-world problems. The course teaches about pointers, dynamic storage, recursion, sorting, and more, helping students gain the ability to analyze and measure program efficiency.
Data Structures Fundamentals
This course covers data structures essential for designing efficient algorithms, 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 basic programming concepts, object-oriented programming, and algorithms.
Data structures and algorithms I: ArrayLists, LinkedLists, stacks and queues
The Data Structures and Algorithms course reviews key Java techniques and introduces time complexity. Covers arrays, linked lists, and their use in implementing ADTs such as stacks, queues, and deques, emphasizing recursion and amortized analysis.
Data Structures and Algorithms II: Binary Trees, Heaps, Jump Lists, and Hash Maps
This course is an extension of the previous course and covers hierarchical and non-linear data structures such as trees, binary search trees (BST), binary heaps, HashMaps and SkipLists. Emphasizes time complexity, with a focus on tree properties, BST operations, heap access, and collision strategies in HashMaps.
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