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.
Overview
Syllabus
- 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
