Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
This course is part of the Data Science Foundations: Data Structures and Algorithms Specialization
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About this Course
Completion of the previous course. Calculus, probability theory: distributions, expectations and moments. Some programming experience with Python.
What you will learn
Define basic tree data structures and identify algorithmic functions associated with them
Execute traversals and create graphs within a binary search tree structure
Describe strongly connected components in graphs
Skills you will gain
- Analysis of Algorithms
- Algorithm Design
- Python Programming
- Data Structure Design
- Graphs Algorithms
Completion of the previous course. Calculus, probability theory: distributions, expectations and moments. Some programming experience with Python.
Offered by
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Syllabus - What you will learn from this course
Binary Search Trees and Algorithms on Trees
Basics of Graphs and Graphs Traversals
Union-Find Data Structures and Spanning Tree Algorithms
Shortest Path Algorithms
Reviews
- 5 stars82.14%
- 4 stars14.28%
- 3 stars3.57%
TOP REVIEWS FROM TREES AND GRAPHS: BASICS
This course is easy to understand and implement. It needs more programming exercises further!
very solid course - would love more programming assignments and tougher final
I have grade 100% My mail id- freespace644@gmail.com
Great lecturer and course materials. Assignments were fun also
About the Data Science Foundations: Data Structures and Algorithms Specialization

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