Roadmap to Data Structures and Algorithms Mastery (Java) Phase 1: Fundamentals     Java Basics Ensure you have a solid grasp of:         - Variables, data types, operators         - Control flow (if/else, loops)         - Functions/methods         - Object-Oriented Programming concepts (classes, objects, inheritance, polymorphism) - Free Resources:     - Java Programming for Beginners - https://www.w3schools.com/java/     - Codecademy: https://www.codecademy.com/learn/learn-java Free Resources :-     - GeeksforGeeks - Time Complexity - https://www.geeksforgeeks.org/time-complexity-and-space-complexity/ - Introduction to Big O Notation (YouTube Video) - https://youtu.be/mV3wrLBbuuE?feature=shared Intro to Algorithms & Time/Space Complexity: Understand the principle of analyzing code.    - How to measure efficiency (Big O notation)     - Time complexity vs. space complexity tradeoffs Phase 2:  Core Data Structures     Arrays:-         - One-dimensional and multi-dimensional arrays         - Operations (insertion, deletion, searching, traversal) Linked Lists:-     - Singly linked lists, doubly linked lists     - Implementation and operations Stacks:-     - LIFO (Last In, First Out) principle     - Implementation and applications (e.g., function call stacks) Queues:-     - FIFO (First In, First Out) principle     - Implementation and application (e.g., task scheduling) Trees:-     - Binary trees, binary search trees (BSTs)     - Insertion, searching, traversal (preorder, inorder, postorder) Hash Tables:-     - Hash functions, collision resolution     - Use cases (dictionaries, fast lookups) Free Resources:- Data Structures on GeeksforGeeks: - https://www.geeksforgeeks.org/data-structures/ -Visualizations:-  https://visualgo.net/en Practice Problems:-     - LeetCode: https://leetcode.com/ - Filter by 'Data Structure' tags     HackerRank: https://www.hackerrank.com/ Phase 3: Algorithms     Sorting Algorithms:         - Bubble sort, selection sort, insertion sort, merge sort, quicksort         - Time and space complexity analysis   Searching Algorithms:         - Linear search, binary search, jump search Graph Algorithms     - Breadth-first search (BFS),    - Depth-first search (DFS) Dynamic Programming     - Breaking down problems into overlapping subproblems, memorization Free Resources - Algorithms on GeeksforGeeks:- https://www.geeksforgeeks.org/fundamentals-of-algorithms/ -TopCoder (Algorithm Tutorials):- https://www.topcoder.com/community/data-science/data-science-tutorials/ Phase 4: Advanced Concepts (Optional, but highly recommended) General Tips: - Consistency is Key: Dedicate practice time daily or regularly. - Think, Then Code: :Understand concepts before jumping into implementation. - Visualize:  Draw diagrams! - Solve Problems and Challenges:-  Practice is how you solidify concepts. - Project-Based Learning:-  Build small projects that use the DSA you've learned. Let me know if you'd like specific resources in advanced areas!