Core Data Structures and Algorithms Using Pseudocode

Many programming courses teach you syntax, but truly understanding how data is managed and manipulated is key to solving complex problems. This course focuses on demystifying the essential building blocks of computer science. By focusing on clear, written explanations of the step-by-step logic, you will move beyond simply memorizing code snippets. You will gain a deep, transferable understanding of fundamental data structures and classic algorithms, enabling you to write more performant and scalable code regardless of the programming language you use. What you'll learn: * Understand the principles of foundational linear structures like Stacks and Queues and their practical applications. * Master graph traversal techniques, including Depth-First Search (DFS) and Breadth-First Search (BFS). * Analyze the logic and complexity of essential sorting algorithms (e.g., Merge Sort, Quick Sort). * Apply advanced graph algorithms, such as Dijkstra's algorithm for finding the shortest path. * Practice reading and writing clean, language-agnostic pseudocode for any algorithm implementation. * Learn how to calculate and interpret Big O notation to evaluate algorithmic performance and efficiency. The course begins by establishing core definitions and concepts, then systematically breaks down each structure and algorithm using detailed, written pseudocode examples. We conclude with analysis focusing on performance trade-offs and practical application contexts. This course is designed for absolute beginners in computer science and programming who wish to build a solid foundational knowledge of algorithms. No prior experience with specific programming languages or advanced math is required. Start building your essential computer science foundation today.