Introduction to Data Structures and Algorithms

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What Will You Learn?

This OOP introduction covers key data structures (stacks, queues, linked lists), advanced dictionaries (skip-lists, hashing), and various trees (binary search trees, 2-4 trees, red-black trees). It delves into priority queues, heaps, and sorting algorithms (merge, quick, radix). The graph section includes BFS, DFS, connected components, spanning trees (Prim's, Kruskal’s), and Dijkstra’s algorithm for shortest paths. Directed acyclic graphs are covered via topological sort and finding the longest path. This concise overview provides a foundation in OOP, diverse data structures, and essential algorithms for problem-solving.

About This Course

Provider: NPTEL
Format: Online
Duration: 36 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: Able to gain solid understanding of data structure and algorithms after completing this free course
Course Prerequisites: Basic Understanding of Data Structure
Assessment and Certification: NA
Instructor: IIT Delhi
Key Topics: Data Structure, Algorithms, Data Science
Topic Covered: 
  1. - Introduction to object oriented programming
  2. - stacks, queues and linked lists
  3. - skip-lists, hashing, analysis of collision resolution techniques
  4. - Trees, traversals, binary search trees
  5. - optimal and average BST’s trees and red-black trees
  6. - Tries and pattern matching. 
  7. - Priority queues and binary heaps
  8. - Sorting: merge, quick, radix, selection, heap 3
  9. - Introduction to Graphs, Breadth first search and connected components
  10. - Depth first search in directed and undirected graphs and strongly connected components
  11. - Spanning trees: Prim's and Kruskal's algorithm, union-find datastructure.
  12. - Dijkstra's algorithm for shortest path. shortest path tree.
  13. - Shortest and longest paths in directed acyclic graphs

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