Data Structures & Algorithm

About Course

The DSA course typically refers to the Data Structures and Algorithms course, which is a fundamental component of computer science and programming education. It focuses on teaching students about various data structures and algorithms and their applications in solving computational problems efficiently.

CAD DESK delivers quality training invites the students to do Internships and work on projects during the online classes. Data structures are ways of organizing and storing data in memory, such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Algorithms, on the other hand, are step-by-step procedures or methods for solving specific problems. They involve manipulating data structures and performing operations on them to achieve desired results.

Topics Include

• Introduction to Algorithms and Analysis
  • Introduction to algorithms, algorithm analysis, and complexity theory.
  • Asymptotic notations (Big O, Big Omega, and Big Theta).
  • Time and space complexity analysis.
• Arrays and Strings
  • Arrays and their properties
  • String manipulation and algorithms
  • Dynamic arrays and amortized analysis
• Linked Lists
  • Singly linked lists, doubly linked lists, and circular linked lists.
  • Linked list operations (insertion, deletion, searching)
  • Linked list variations (skip lists, self-adjusting lists)
• Stacks and Queues
  • Stack and queue data structures
  • Implementations, operations, and applications
  • Array-based and linked list-based implementations
• Trees
  • Binary trees and binary search trees
  • Balanced binary search trees (AVL trees, red-black trees)
  • Tree traversal algorithms (pre-order, in-order, post-order)
  • Heap data structure and heap sort algorithm
• Hashing and Hash Tables
  • Hashing principles and collision resolution techniques
  • Hash table implementation and operations
  • Load factor, rehashing, and performance analysis
• Graphs and Graph Algorithms
  • Graph representation (adjacency matrix, adjacency list)
  • Graph traversals (DFS, BFS)
  • Shortest path algorithms (Dijkstra's algorithm, Bellman-Ford algorithm)
  • Minimum spanning tree algorithms (Prim's algorithm, Kruskal's algorithm)
• Sorting Algorithms
  • Comparison-based sorting algorithms (bubble sort, insertion sort, selection sort)
  • Divide and conquer algorithms (merge sort, quicksort)
  • Radix sort, counting sort, and bucket sort
• Problem-Solving Techniques
  • Problem-solving strategies and approaches
  • Analyzing problem constraints and designing algorithms
  • Practice with algorithmic problem-solving

Course Duration: 45 days