In this module, we will explore the foundational concepts of time and space complexity and their role in evaluating algorithms. You’ll learn how to calculate time and space complexity for both iterative and recursive algorithms through practical examples. By the end of this module, you will have a strong grasp on Big O notation and how it’s used in interviews to assess algorithm efficiency.

In this module, we will dive into the theory behind arrays, exploring their efficiency and common limitations. You’ll also learn essential Java array methods and their practical applications. Alongside theory, we’ll tackle a range of Leetcode practice problems that focus on array manipulation, from finding maximum sums to solving Sudoku, ensuring you’re prepared for technical interviews.

In this module, we will explore the theory and practice of sorting algorithms, from basic methods like Bubble Sort and Selection Sort to more advanced techniques like Merge Sort and Quick Sort. You will implement these algorithms in Java and understand their inner workings. Additionally, we’ll solve Leetcode practice problems to reinforce your skills in applying sorting algorithms to real-world coding challenges.

In this module, we will explore the structure of linked lists, from the basics of singly linked lists to the more advanced doubly linked lists. You will learn to implement, iterate, and modify linked lists using Java. Additionally, we will dive into practical problems, solving real-world challenges like detecting cycles, reversing lists, and merging lists, providing hands-on experience with this essential data structure.

In this module, we will explore the core concept of hash tables, how they function, and their practical applications in solving algorithmic problems. You’ll learn about collision resolution, different types of hash tables, and how to leverage them to solve real-world problems. Through Leetcode practice problems, you’ll gain hands-on experience applying hash tables to challenges like detecting duplicates, grouping anagrams, and finding missing integers.

In this module, we will introduce the stack data structure and its critical role in various algorithms and applications. You’ll learn how to implement stacks in Java and use them to solve real-world problems, including evaluating mathematical expressions and finding the next greater element. With practice problems from Leetcode, you’ll gain hands-on experience solving challenging tasks using stacks effectively.

In this module, we will introduce the queue data structure, explaining its key features and applications in algorithms. You’ll learn how to implement a queue in Java, both through arrays and linked lists, and explore how to use it for efficient data management. By the end of this module, you will be well-equipped to use queues in various coding challenges and problem-solving contexts.