Data Structures and Algorithms in Java for Coding Interviews

Preparing for technical interviews or trying to write efficient software can feel overwhelming without a solid grasp of computer science fundamentals. Understanding how data is stored, organized, and manipulated is the key to writing optimized code and solving complex programming challenges. This text-based course guides you through the foundational concepts of data structures and algorithms using Java. You will learn to analyze algorithmic complexity, implement core data structures from scratch, and apply modern Java features to write clean, type-safe, and highly performant code. What you'll learn: - Understand the foundational principles of Big O notation and how to analyze time and space complexity. - Build essential linear data structures including arrays, linked lists, stacks, and queues from scratch. - Master hierarchical and self-balancing search trees, such as Binary Search Trees, AVL trees, and Red-Black trees. - Implement efficient hashing mechanisms, hash maps, heaps, and priority queues using modern Java collections. - Apply core sorting and substring search algorithms, from classic bubble sort to advanced quicksort and Rabin-Karp. - Practice writing type-safe, reusable data structures using Java Generics and modern programming standards. The course begins with essential terminology, abstract data types, and complexity analysis before moving into hands-on implementations. You will progress systematically from simple linear structures to complex self-balancing trees, sorting routines, and interview-style algorithmic problems. This course is designed for beginner programmers, computer science students, and self-taught developers who want to build a strong theoretical and practical foundation in Java algorithms without any prior computer science background. Start reading today to build your algorithmic thinking and take the next step toward passing your technical interviews.