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💻Graph Algorithms with Python BFS DFS Dijkstra and Minimum Spanning Trees hero

Level: Beginner

💻Graph Algorithms with Python BFS DFS Dijkstra and Minimum Spanning Trees

Master graph algorithms in Python: BFS, DFS, Dijkstra, and Minimum Spanning Trees, plus Union Find. Build a City Route Planner that finds shortest routes and detects unreachable zones. Just basic Python needed.

5.0

5.1k+ learners

Duration

4 hr 15 min

Learners

5.1k+ Enrolled Students

Session Recording

Lifetime Access

Post Session

Mentor support

Session Schedule

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₹499

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Course Fee

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₹499

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Includes

• Expert Designed Curriculum

• Doubt Clearing Session

• Forever Community Access

After this course, you can

Implement graph algorithms

Find shortest paths efficiently

Build minimum spanning trees

Solve graph interview problems

Course Curriculum

Expand or explore the full learning path.

Lessons

Start here after enrolling. These lessons form the core learning path for the course.

What a Graph Really Is: Friends, Maps, and the Internet

Directed vs Undirected: One-Way Streets and Two-Way Friendships

Weighted Graphs: When Edges Have a Price

Adjacency Matrix: The Grid Approach, and Its Memory Cost

Adjacency List: The Dictionary Approach Python Loves

Build It: A Reusable Graph Class You'll Use All Course

Why Traversal Is the Heart of Every Graph Problem

BFS: Exploring Level by Level with a Queue

BFS in Python, Plus Shortest Path in Unweighted Graphs

DFS: Going Deep with Recursion and with a Stack

Visited Sets: The Bug Every Beginner Hits Once

BFS vs DFS: Picking the Right Tool

The Problem: What to Do First When Tasks Depend on Each Other

DAGs: Why Cycles Ruin Everything

Kahn's Algorithm: In-Degrees and the Queue

DFS Topological Sort: The Finish-Time Trick

Detecting Impossible Orderings (Cycle Detection as a Bonus)

Mini Project: A Course Prerequisite Planner

Why BFS Is Not Enough Once Weights Show Up

Dijkstra: The Greedy Classic with a Priority Queue

Bellman-Ford: Handling Negative Weights, Catching Negative Cycles

Floyd-Warshall: Every Pair at Once with 3 Loops

A*: Dijkstra with a Sense of Direction

Choosing the Right Algorithm: A Decision Cheat Sheet

The MST Problem: Wiring Cities Without Wasting Cable

Prim's Algorithm: Growing a Tree with a Heap

Disjoint Sets: The "Who's in Your Group" Structure

Union by Rank and Path Compression: Near-O(1) Magic

Kruskal's Algorithm: Sort Edges, Union Sets

Prim vs Kruskal, and Union Find Beyond MST

Connected Components: Counting Friend Circles

Cycle Detection: Directed vs Undirected, Two Different Tricks

Bipartite Graphs: The Two-Color Test

Grid and Island Problems: 2D Arrays Are Secretly Graphs

Pattern Recognition: Mapping a Problem to an Algorithm

Capstone: The City Route Planner

Live Session Content

This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.

Post Session Study Material

This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.

Daily Coding Practice Set

30 min

Algorithm Pattern Exercises

25 min

Algorithm Pattern Notes

15 min

Complexity Analysis Guide

20 min

Interview Preparation Problem Set

45 min

Competitive Programming Practice

45 min

Algorithm Pattern Mastery Series

45 min

Competitive Coding Challenge Set

30 min

Requirements

What you should have before starting the course.

Basic Python programming knowledge

Familiarity with basic data structures

Understanding of Big-O notation

Willingness to solve graph problems

Tools you are going to use

C++

C++

Python

Python

Codeforces

Codeforces

LeetCode

LeetCode

HackerRank

HackerRank

Learn From Expert Instructor

Meet the mentors leading the live sessions.

Aarav Sharma

Aarav Sharma

Senior Frontend Engineer, StudioLabs

Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.

LinkedIn
Ananya Mehta

Ananya Mehta

Design Technologist, CraftLabs

Ananya blends design and code to help learners ship portfolio-ready projects.

LinkedIn
Kabir Sayed

Kabir Sayed

Frontend Mentor, PixelWorks

Kabir focuses on clean code, accessibility, and practical frontend delivery.

LinkedIn

You should join this course if you

Students & Fresh Graduates

Build a strong portfolio

Learn from live mentors

Get feedback on your work

Working Professionals

Upgrade frontend skills

Ship real projects

Join a peer community

Career Switchers

Structured learning path

Hands-on practice

Guided sessions

Freelancers & Creators

Build client-ready sites

Improve delivery speed

Learn modern workflows

What you will get after completing this course

Completion certificate

Receive an official course completion certificate

Earn skill-focused feedback from mentors

Showcase your project in the Shattak community

Access lifetime notes and references

Stay connected with instructors for guidance

Completion bonus

Certificate access, community showcase, and lifetime mentor guidance.

Hear From Learners Who've Taken This Course

Honest feedback from learners who completed the live sessions.

4.8

24

Clear structure, solid examples, and a fast pace that keeps you engaged.

Riya Jain

Riya Jain

B.Tech, NIT Trichy

4.6

18

Practical sessions with feedback that helped improve my portfolio.

Kabir Singh

Kabir Singh

Frontend Intern, PixelWorks

4.9

12

Loved the structure and the live walkthroughs.

M

Meera Patel

Design Graduate

See what they have build

ZS

Zainab Shaikh

Portfolio Landing Page

Portfolio Landing Page

300 Likes

View Live
DS

Devendra Singh

Product Marketing Site

Product Marketing Site

214 Likes

View Live
NA

Nadia Ahmed

Interactive Web Story

Interactive Web Story

183 Likes

View Live

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Frequently Asked Questions

Starting From

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Duration

4 hr 15 min

Get Life Time Access

₹0

₹499

100% off

Get Life Time Access

₹0

₹499

100% off