Foundations of Algorithms and Data Structures

Writing efficient software requires more than just knowing a programming language; it demands a solid grasp of how data is organized and processed. This text-based course guides you through the core concepts of algorithms and data structures without overwhelming jargon. You will transition from writing basic scripts to designing optimized, high-performance programs. By understanding how to measure code performance using Big O notation, you will learn to choose the right tools and strategies for any computational problem. What you'll learn: - Understand fundamental data structures including arrays, linked lists, stacks, queues, and graphs. - Implement essential sorting and searching algorithms to manipulate data efficiently. - Apply dynamic programming techniques to break down and solve complex, recursive problems. - Analyze time and space complexity using Big O notation to evaluate your code's efficiency. - Write clean, readable implementations of classic algorithms using modern programming practices. The course begins with foundational definitions of algorithmic complexity and basic data structures, then progresses step-by-step through advanced sorting, searching, graph traversal, and dynamic programming. You will reinforce your reading with written exercises and clear code examples designed to solidify your understanding. This course is designed for beginner programmers, computer science students, and self-taught developers who want to build a strong theoretical and practical foundation, with no prior algorithm experience required. Start reading today to unlock the core principles of computer science and elevate your coding skills.