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Computer Programming

16768 learners

Mastering Graphs in Python

This course is designed to demonstrate the representation of a graph using adjacency graphs and adjacency matrices in Python. A core part of the course is dedicated to implementing and utilizing BFS and DFS algorithms in graphs. Explore the comprehensive use of graph data structures in solving intricate interview-based algorithmic problems.

Python

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6 lessons

18 practices

3 hours

Computer Science Fundamentals

Lessons and practices

Lesson 1: Building and Analyzing Graphs with the Adjacency Matrix

Exploring Social Network Connections with an Adjacency Matrix

Change the Social Network Connections

Debugging the Friend Suggestions Algorithm

Adding Overlapping Teams Relationships Using an Adjacency Matrix

Lesson 2: Building and Analyzing Graphs with the Adjacency List

Building and Manipulating a Social Network with Adjacency Lists

Adding a New Band Collaboration to the Graph

Fixing the Bus Route Map

Adding a New Route to the Tour Map

Lesson 3: Understanding and Implementing Depth-First Search (DFS) for Graphs

Exploring States with Depth-First Search

Adjusting the Start Node for DFS Traversal

Debug and Correct the DFS Traversal

Implementing DFS Traversal for University Courses

Lesson 4: Discovering Connected Components in a Graph Using Depth-First Search

Undirected Graph Cycle Counting Algorithm Creation

Lesson 5: Unveiling the Breadth-First Search Algorithm for Graph Traversal

Breadth-First Search in Action: Organizing a Space Party

Changing the Starting Point of BFS Traversal

Debugging BFS Traversal Algorithm

Implementing BFS Traversal from a Specific Start Node

Lesson 6: Finding the Shortest Path in Graphs with BFS Algorithm

Interstellar Shortest Path Finding in a Connected Graph

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