Data Structures and Algorithms: In-Depth DSA using Python | Udemy [Update 11/2025]
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Genre: eLearning[/center]
Learn Python Data Structures, Algorithms (DSA) with Animated Examples, includes Dynamic Programming, Backtracking etc...
What you'll learn:
[list]
[*]Learn Data Structures, Abstract Data Types and their implementation in Python
[*]Implementation of Searching Algorithms in Python
[*]Implementation of Stacks, Queues, Linked List, Binary Trees, Heaps and Graphs in Python
[*]Implementation of Binary Tree Traversal Techniques in Python
[*]Graph traversals techniques ie Depth First Search and Breadth-First Search in Python
[*]Implementation of Sorting Algorithms in Python
[*]Enhance Analytical Skill and efficiently use searching and sorting algorithms in real applications
[/list]
This course will help you in better understanding of the basics of Data Structures and how algorithms are implemented in Python. This course consists of Videos which covers the theory concepts + implementation
in python
.
There's tons of concepts and content in this course:
_Basics of data structures & Algorithms_
_Analysis of Algorithms (Big O, Time and Space complexity)_
_Recursion & Analysis of Recursive Algorithms_
_Searching Algorithms_
_Sorting Algorithms_
_Linked List_
_Stacks_
_Queues_
_Binary Trees_
_Binary Search Trees_
_Balanced Binary Search Trees_
_Priority Queues and Heaps_
_Hashing_
_Graphs_
_Graph Traversal Algorithms_
Followed by Advanced Topics of Algorithms:
_Sets and Disjoint Sets_
_Divide and Conquer Approach - Introduction_
_Divide and Conquer - Binary Search_
_Divide and Conquer - Finding Maximum and Mininum_
_Divide and Conquer - Merge Sort_
_Divide and Conquer - Quick Sort_
_Divide and Conquer - Selection Algorithm_
_Divide and Conquer - Strassens Matrix Multiplication_
_Divide and Conquer - Closest Pair_
_Divide and Conquer - Convex Hull_
_Greedy Method - Introduction_
_Greedy Method - Knapsack Problem_
_Greedy Method - Job Sequencing with Deadlines_
_Greedy Method - Mininum Cost Spanning Tree (Prim's & Kruskal's Algorithms)_
_Greedy Method - Optimal Storage on Trees_
_Greedy Method - Optimal Merge Pattern_
_Greedy Method - Single Source Shortest Path (Dijkstra's Algorithm)_
_Dynamic Programming - Introduction_
_Dynamic Programming - Multistage Graphs_
_Dynamic Programming - All Pairs Shortest Path_
_Dynamic Programming - Single Source Shortest Path_
_Dynamic Programming - Optimal Binary Search Trees_
_Dynamic Programming - 0/1 Knapsack Problem_
_Dynamic Programming - Reliability Design_
_Dynamic Programming - Travelling Salespersons Problem_
_Backtracking - Introduction_
_Backtracking - n-Queesn Problem_
_Backtracking - Sum of Subsets Problem_
_Backtracking - Graph Coloring Problem_
_Backtracking - Hamiltonian Cycles Problem_
_Backtracking - 0/1 Knapsack Problem_
_Branch & Bound - Introduction_
_Branch & Bound - n-Queens Problem_
_Branch & Bound - Job Sequencing Problem_
_Branch & Bound - 0/1 Knapsack Problem_
Again, each of these sections includes detailed videos tutorial.
Who this course is for:
Students who want to have better understanding of Data Structures
Python programmers curious about Data Structures
IT Professional experimenting implementation of Data Structures in Python
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