Master Important Data Structures and Algorithms in Java.

Explore linked list operations in Java, including creation, insertion, updating, reading, and deletion of elements. Learn to use get, set, remove, and offer for list elements.

Explore vector operations in Java, including creating a vector with initial capacity 10, inserting, updating, reading by index, removing elements, and iterating with an iterator.

Explore stack operations in Java by creating a static stack, inserting and updating elements with push and item methods, reading and peeking at top, and deleting using pop or remove.

Explore the internal implementation of a queue using a linked list, with front and rear pointers managing insertions and removals behind the scenes.

Demonstrate building a priority queue of integers in java and performing insertions with offer (and add), then remove and poll, and inspect the front element with peek.

Java hash sets store unique elements, do not preserve order, allow nulls, and use hash codes and equals for fast lookup, spell checking, with capacity 16 and load factor 0.75.

Explore how a hash set is implemented via a map, where each element becomes a key and a default value like present is stored.

Demonstrate sorting values from a set by converting to a list and sorting it, showing how an unordered set affects output order and how a list-based sort resolves it.

Explore the internal implementation of LinkedHashSet by examining its LinkedHashMap-based structure, including the entry class and before and after links, and the insertion and access order.

Explore TreeSet code challenge 1 and its solution by creating a set, adding strings, and printing sorted results, contrasting with prior linked-list approaches.

Explore the hash map data structure in Java, including definition, properties, declaration options with initial capacity and load factor, and constant-time retrieval of unique keys in an unordered, non-synchronized store.

Explore the internal implementation of a hashmap, including hashing and equals for inserts, bucket indexing, linked lists and treeification, collision handling, and get operations.

Explore a hashmap code challenge 1 solution by counting the frequency of each character in a string, using a map of character keys to integer values, then printing the results.

Convert a HashMap to a TreeMap in Java by solving the HashMap code challenge and reviewing the solution, with practical map entries and a runnable example.

Explore linked hash map concepts, including insertion order, unique keys, and null handling, and see how it combines a hash map with a doubly linked list to maintain element order.

Explore LinkedHashMap in Java by creating maps, inserting data with put, retrieving with get, and removing or updating entries, while understanding order and essential methods.

Explore how LinkedHashMap uses access order versus insertion order to implement least recently used behavior, with a code demo showing how get operations reshuffle entries and drive LRU cache concepts.

Examine the internal implementation of a tree map as a self-balancing binary search tree with a red-black tree. See how colors, rotations, and rebalancing preserve tree properties.

Learn to implement CRUD operations on a Java TreeMap, using put, get, update, and remove, with ascending order and exploration of descending map, ceiling key, and higher key methods.

Explore how a hash table provides synchronized storage, no null keys or values, its internal implementation, and when to use it versus a concurrent hash map in Java.

Explore essential hash table methods in Java, including insert with put, fetch with get, remove, update, and queries like contains, clone, clear, and compute, noting the synchronized behavior of Hashtable.

Develop a Java program to find all symmetric pairs from a given array of numbers using a hash table, and print the identified symmetric pairs.

Explore the tree data structure, its properties, implementations, and when to use it, including root and leaf nodes, left and right children, height, levels, and basic internal representation.

Explore the binary tree data structure, its properties (at most two children), and Java implementation. Understand root, left and right children, leaves, and level-based node counts.

Implement level order traversal of a binary tree using a queue to print nodes level by level from root to leaves, with a Java implementation and O(n) time.

Learn to implement pre-order tree traversal using a stack to iteratively visit nodes in root-left-right order by pushing right child before the left, ensuring the left subtree is processed first.

This lecture explains implementing a post-order traversal of a binary tree in Java using a stack, visiting left, right, then root, and printing nodes as they are popped.

Master the binary search tree in Java, understanding its left-subtree values less than the root and right-subtree values greater, with no duplicates, and node-based implementation with search, insert, and delete.

Learn to implement a max heap in java, inserting elements to maintain the max-heap property where the root is the maximum and each parent exceeds its children.

Master the graph adjacency matrix implementation in Java by building a two dimensional array, marking edges as one for connections, ensuring symmetry for undirected graphs, and printing the adjacency matrix.

Implement an adjacency list for an undirected graph using an array of linked lists. Add edges, print the adjacency, and compare space efficiency with adjacency matrices and time complexity O(V+E).

Count total paths from a source to a destination in a directed graph using backtracking and recursion, while avoiding cycles with a visited array.