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Foundations of Programming: Data Structures and Algorithms for Developers

A course designed to empower aspiring software developers. Master essential data structures such as arrays, trees, and graphs, and implement key algorithms for sorting and searching. Through theoretical insights and practical exercises, enhance your coding proficiency and tackle complex computational problems with ease. Perfect for those looking to elevate their programming skills and optimize application performance.

4.0

4033 ratings
60,458 students enrolled
₹13,000
₹18,000
27% off

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Course content

  • Array basics: declaration, initialization, accessing elements.
  • Array operations: insertion, deletion, updating elements.
  • Searching in arrays: linear search, binary search.
  • Sorting arrays: various sorting algorithms like bubble sort, selection sort, insertion sort, merge sort, quick sort.
  • Array manipulation techniques: reversing, rotating, finding duplicates, finding missing elements.
  • Singly Linked Lists: structure, traversal, insertion, deletion, searching.
  • Doubly Linked Lists: structure, traversal, insertion, deletion, searching.
  • Circular Linked Lists: structure, traversal, insertion, deletion, searching.
  • Linked List operations: concatenation, splitting, reversing.
  • Special types of Linked Lists: Skip lists, XOR linked lists.
  • Deque (Double-ended queue): structure, operations, implementation.
  • Stack basics: structure, operations (push, pop, peek), implementation using arrays and linked lists.
  • Stack applications: expression evaluation, function call stack, undo mechanisms.
  • Queue basics: structure, operations (enqueue, dequeue, peek), implementation using arrays and linked lists.
  • Queue applications: BFS traversal, priority queues, scheduling algorithms.
  • String basics: string representation, string operations.
  • String manipulation techniques: concatenation, substring, string reversal, string comparison.
  • Pattern matching: brute force pattern matching, Knuth-Morris-Pratt (KMP) algorithm.
  • Binary Tree basics: structure, traversal (inorder, preorder, postorder), height, depth.
  • Binary Search Trees (BST): insertion, deletion, searching, balancing.
  • AVL Trees: balancing, rotations, insertion, deletion.
  • Red-Black Trees: properties, balancing, insertion, deletion.
  • Tree traversal algorithms: level order traversal, breadth-first search (BFS), depth-first search (DFS).
  • Heap basics: structure, heap properties (min-heap, max-heap).
  • Heap operations: insertion, deletion (extract min, extract max), heapify.
  • Heap applications: priority queues, heap sort algorithm.
  • Hash table basics: structure, hash function, collision resolution techniques (chaining, open addressing).
  • Hash map: key-value pairs, operations (insertion, deletion, searching).
  • Hash set: set of unique elements, operations (insertion, deletion, searching).
  • Hashing applications: caching, symbol tables.
  • Graph representation: adjacency matrix, adjacency list.
  • Graph traversal: breadth-first search (BFS), depth-first search (DFS).
  • Shortest path algorithms: Dijkstra's algorithm, Bellman-Ford algorithm.
  • Minimum spanning tree algorithms: Prim's algorithm, Kruskal's algorithm.
  • Topological sorting.
  • Graph coloring, bipartite graphs.
  • Linear Search
  • Binary Search
  • Bubble Sort
  • Selection Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
  • Coin Change
  • Fractional Knapsack
  • Job Sequencing
  • Fibonacci Series
  • Knapsack Problem
  • Longest Common Subsequence
  • Subset Sum
  • Longest Increasing Subsequence
  • Maximum Subarray
  • N-Queens Problem
  • Subset Sum
  • Dijkstra's Algorithm
  • Bellman-Ford Algorithm
  • Floyd-Warshall Algorithm
  • Trie (Prefix Tree)
  • Segment Tree
  • Disjoint Set Union (Union-Find)
  • Prefix function and pattern matching
  • Time complexity analysis
  • String searching algorithm
  • Time complexity analysis
  • Advanced trie applications (e.g., Ternary Search Tries)
  • Applications (e.g., spell checker, IP routing)
  • Basic Bitwise Operations
  • Bitwise Manipulation Techniques
  • Big O Notation
  • Space Complexity
  • Two Sum
  • Merge Two Sorted Lists
  • Remove Duplicates from Sorted Array
  • Remove Nth Node From End of List
  • Min Stack
  • Implement Queue using Stacks
  • Reverse Linked List
  • Design Circular Queue
  • Maximum Depth of Binary Tree
  • Validate Binary Search Tree
  • Binary Tree Level Order Traversal
  • Symmetric Tree
  • Merge k Sorted Lists
  • Find Median from Data Stream
  • Binary Tree Zigzag Level Order Traversal
  • Last Stone Weight
  • Two Sum
  • Kth Largest Element in an Array
  • Top K Frequent Elements
  • Kth Smallest Element in a Sorted Matrix
  • Course Schedule
  • Longest Substring Without Repeating Characters
  • Group Anagrams
  • Graph Valid Tree
  • Merge Intervals
  • Number of Islands
  • Network Delay Time
  • The Skyline Problem
  • Find First and Last Position of Element in Sorted Array
  • Sort Characters By Frequency
  • Minimum Window Substring
  • Word Ladder
  • Climbing Stairs
  • House Robber
  • Coin Change
  • Decode Ways
  • Maximum Subarray
  • Reverse Pairs
  • Maximum Product Subarray

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4.7

4033 ratings

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