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⏱ 2h 54m📚 29 lessons
Graph Theory for Competitive Programming
Learn fundamental graph algorithms and data structures to solve challenging informatics and math problems for competitive programming.
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About this course
Do you want to enhance your problem-solving skills for informatics and math competitions? This course provides a practical approach to mastering graph theory, a crucial area for success in competitive programming. You will develop essential algorithmic thinking and gain the confidence to tackle a wide range of competition problems.
This course will equip you with the foundational knowledge and practical techniques needed to excel in competitive programming. By understanding graph structures and algorithms, you will transform your approach to complex problems and significantly improve your performance in contests.
What you'll learn:
- Understand the fundamental concepts and terminology of graph theory.
- Master algorithms for graph traversal, such as Breadth-First Search (BFS) and Depth-First Search (DFS).
- Apply algorithms for finding shortest paths, including Dijkstra's and Bellman-Ford.
- Learn about minimum spanning trees and their applications.
- Explore algorithms for network flow and matching problems.
- Practice implementing graph algorithms to solve common competitive programming challenges.
The course begins with core definitions and progresses through essential graph algorithms and their applications in problem-solving, preparing you for various levels of competition.
This course is designed for beginners with no prior experience in graph theory, making it ideal for students preparing for informatics and mathematics olympiads. No advanced mathematical or programming knowledge is required.
Start building your competitive programming prowess with graph theory today.
What you'll get
📜Certificate of completion Add it to your LinkedIn profile
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💸14-day refund No questions asked
⚡Short & focused 2h 54m of practical content
Certificate of completion
Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.