University of Colorado Boulder - Trees and Graphs: Basics
- Offered byCoursera
Trees and Graphs: Basics at Coursera Overview
Duration | 34 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Trees and Graphs: Basics at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 2 of 3 in the Data Structures and Algorithms Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Advanced Level Completion of the previous course. Calculus, probability theory: distributions, expectations and moments. Some programming experience with Python.
- Approx. 34 hours to complete
- English Subtitles: English
Trees and Graphs: Basics at Coursera Course details
- 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.
- Trees and Graphs: Basics can be taken for academic credit as part of CU Boulder?s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder?s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
Trees and Graphs: Basics at Coursera Curriculum
Binary Search Trees and Algorithms on Trees
Binary Search Trees -- Introduction and Properties
Binary Search Trees -- Insertion and Deletion
Red-Black Trees Basics
Red-Black Trees -- Rotations/Algorithms for Insertion (and Deletion)
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Important Prerequisites
Logistics: Textbook and Readings
Overview of Module 1
Reading CLRS Chapter 12
CLRS Chapter 12.1-12.3
CLRS Chapter 13 - 13.1
CLRS Chapter 13.2 - 13.3
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Basics of Binary Search Trees
Binary Search Tree: Insert and Delete
Red-Black Tree Basics
Tree Rotations
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Basics of Graphs and Graphs Traversals
Graphs and Their Representations
Graph Traversals and Breadth First Traversal
Depth First Search Introduction
Depth First Search
Topological Sorting and Applications
Strongly Connected Components - Definitions
Strongly Connected Components - Properties
Strongly Connected Components - Algorithm
Overview of Module 2
CLRS Chapter 22 (Section 22.1)
CLRS Chapter 22 (Section 22.2)
CLRS Chapter 22 (Section 22.3)
CLRS Chapter 22 (Section 22.4
CLRS Chapter 22 (Section 22.5)
Graph Representations
Combined Quiz on Graph Traversals
Topological Sort Graphs
Strongly Connected Components
Union-Find Data Structures and Spanning Tree Algorithms
Amortized Analysis of Data Structures
Amortized Analysis: Potential Functions
Spanning Trees and Minimal Spanning Trees with Applications
Kruskal?s Algorithm for Finding Minimal Spanning Trees
Union-Find Data Structures and Rank Compression
Overview of Module 3
CLRS Chapter 17
CLRS Chapter 23 (Section 23.1)
CLRS Chapter 23 (Section 23.2)
CLRS Chapter 21
Amortized Analysis
Minimum Spanning Tree
Kruskal's Algorithm
Disjoint Set Forest
Shortest Path Algorithms
Shortest Path Problems and Their Properties
Bellman-Ford Algorithm for Single Source Shortest Paths
Shortest Path on DAGs
Dijkstra?s Algorithm for Single Source Shortest Paths with Nonnegative Edge Weights
Proof of Dijkstra's Algorithm
All Pairs Shortest Path Problems and Floyd-Warshall?s Algorithm
Overview of Module 4
CLRS Chapter 24 (up to section 24.1)
CLRS Chapter 24 (Section 24.1)
CLRS Chapter 24 (Section 24.2)
CLRS Chapter 24 (Section 24.3 and 24.5)
CLRS Chapter 25 (Sections 25.1 and 25.2)
Shortest Path Problems Properties
Shortest Path - Bellman Ford Algorithm
Dijkstra's Algorithm
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