Foundations of Algorithms and Data Structures

Every great software application relies on efficient problem-solving patterns. Understanding algorithms and data structures is the key to writing code that scales, runs fast, and solves complex computational challenges. This text-based course guides you from absolute basics to a solid understanding of how to analyze, design, and implement foundational algorithms. You will learn how to evaluate code performance and choose the right data structure for any programming task. What you will learn: Understand core algorithmic concepts, key terminology, and foundational computational models; Analyze code performance using Big O notation to measure time and space complexity; Implement essential data structures including arrays, linked lists, stacks, queues, and hash tables; Apply classic sorting and searching algorithms to organize and retrieve data efficiently; Explore algorithmic paradigms such as recursion, divide-and-conquer, and greedy approaches; Practice solving real-world computational problems through structured written exercises and code examples. We begin with the absolute basics of computational thinking and theoretical foundations before moving on to practical data structures, sorting algorithms, and modern complexity analysis. Each concept is explained clearly through detailed written explanations and step-by-step code walkthroughs. This course is designed for beginner programmers, self-taught developers, and computer science students looking for a solid theoretical and practical foundation. No advanced mathematics or prior algorithms experience is required. Start your journey into computational thinking and build more efficient software today.