Back to Trees and Graphs: Basics
University of Colorado Boulder

Trees and Graphs: Basics

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.

Status: Graph Theory
Status: Tree Maps
AdvancedCourse34 hours

Featured reviews

KK

5.0Reviewed Mar 29, 2022

I have grade 100% My mail id- freespace644@gmail.com

SK

5.0Reviewed Aug 28, 2021

Great lecturer and course materials. Assignments were fun also

PA

5.0Reviewed Aug 20, 2024

The CLRS version for University of Colorado students to access online has some Chapter number changes leading to confusion about what chapter to read in weeks 3 and 4 of this course.

QN

5.0Reviewed Sep 28, 2022

T​his course is easy to understand and implement. It needs more programming exercises further!

DW

4.0Reviewed Sep 12, 2024

Good but some typo's in the quizzes and assignments. Would like to see more thorough exercises

RU

4.0Reviewed Aug 27, 2023

Some typos are not acknowledged. The evaluations are disconnected from the lectures.

BC

4.0Reviewed Jul 2, 2021

very solid course - would love more programming assignments and tougher final

HG

5.0Reviewed May 2, 2023

This course is definitely hard but for some good reason. It stretches the mind of the learner/student to achieve algorithmic nirvana.

MH

5.0Reviewed Jan 1, 2023

Excellent content. Lectures along with textbook provide student with working knowledge of trees and graphs.