Trees and Graphs: Basics
Master fundamental tree and graph algorithms with hands-on implementation in Python for advanced data structures.
Master fundamental tree and graph algorithms with hands-on implementation in Python for advanced data structures.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Foundations of Data Structures and Algorithms Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(104 ratings)
14,533 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Master binary search tree operations and balancing techniques
Implement graph traversal algorithms effectively
Understand strongly connected components in graphs
Develop efficient shortest path algorithms
Analyze and optimize tree and graph algorithms
Skills you'll gain
This course includes:
9.2 Hours PreRecorded video
16 quizzes
Access on Mobile, Desktop, Tablet
FullTime access
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There are 4 modules in this course
This comprehensive course covers fundamental algorithms for tree and graph data structures. Students learn about binary search trees, self-balancing trees, graph traversals, and advanced topics like shortest path algorithms. The curriculum combines theoretical concepts with practical Python implementations, preparing students for real-world algorithm design and analysis challenges.
Binary Search Trees and Algorithms on Trees
Module 1 · 9 Hours to complete
Basics of Graphs and Graphs Traversals
Module 2 · 8 Hours to complete
Union-Find Data Structures and Spanning Tree Algorithms
Module 3 · 7 Hours to complete
Shortest Path Algorithms
Module 4 · 8 Hours to complete
Fee Structure
Instructor
Professor
Sriram Sankaranarayanan is a professor of Computer Science at the University of Colorado Boulder, where he teaches a variety of courses on algorithms, theory of computation, mathematical optimization and programming languages. His research studies how computers can be used to verify and design other computer systems by combining ideas from mathematical logic, theory of computation and control theory. He uses these to analyze "safety-critical" systems ranging from autonomous vehicles to artificial pancreas devices for patients with type-1 diabetes. Sriram obtained a PhD in computer science from Stanford University. Subsequently he worked as a research staff member at NEC research labs in Princeton, NJ. He has been on the faculty at CU Boulder since 2009. Sriram has been the recipient of awards including the CAREER award from NSF, and the Provost's faculty achievement award at CU Boulder.
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4.7 course rating
104 ratings
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