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2024 Faculty Courses School of Computing Department of Mathematical and Computing Science Graduate major in Mathematical and Computing Science

Topological Data Analysis

Academic unit or major
Graduate major in Mathematical and Computing Science
Instructor(s)
Zin Arai / Shinya Nishibata / Masaaki Umehara / Toshiaki Murofushi / Sakie Suzuki / Shunsuke Tsuchioka
Class Format
Lecture (Face-to-face)
Media-enhanced courses
-
Day of week/Period
(Classrooms)
5-6 Tue / 5-6 Fri
Class
-
Course Code
MCS.M427
Number of credits
200
Course offered
2024
Offered quarter
2Q
Syllabus updated
Mar 14, 2025
Language
Japanese

Syllabus

Course overview and goals

We give an introduction to topological data analysis, a method of data analysis that involves topology. As mathematical foundations, we also learn the basics of computational topology and computational geometry.

Course description and aims

The goal is to understand the fundamental concepts of computational topology/geometry and become proficient in applying them to practical topological data analysis.

Keywords

Computational Topology, Computational Geometry, Algorithms

Competencies

  • Specialist skills
  • Intercultural skills
  • Communication skills
  • Critical thinking skills
  • Practical and/or problem-solving skills

Class flow

A report assignment will be announced In the final class.

Course schedule/Objectives

Course schedule Objectives
Class 1 Overview Understand the contents of the lecture.
Class 2 Voronoi and Delaunay Diagrams Understand the contents of the lecture.
Class 3 Weighted Diagrams Understand the contents of the lecture.
Class 4 Diagrams in 3D Understand the contents of the lecture.
Class 5 Alpha Complexes Understand the contents of the lecture.
Class 6 Holes in Spaces Understand the contents of the lecture.
Class 7 Area Formulas Understand the contents of the lecture.
Class 8 Topological Spaces Understand the contents of the lecture.
Class 9 Homology Groups Understand the contents of the lecture.
Class 10 Complex Construction Understand the contents of the lecture.
Class 11 Filtrations Understand the contents of the lecture.
Class 12 PL Functions Understand the contents of the lecture.
Class 13 Matrix Reduction Understand the contents of the lecture.
Class 14 Softwares and Applications 1 Understand the contents of the lecture.
Class 15 Softwares and Applications 2 Understand the contents of the lecture.

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

Not specified.

Reference books, course materials, etc.

Herbert Edelsbrunner, A Short Course in Computational Geometry and Topology, Springer, 2014

Evaluation methods and criteria

By reports.

Related courses

  • MCS.T201 : Set and Topology I
  • MCS.T221 : Set and Topology II
  • MCS.T331 : Discrete Mathematics

Prerequisites

None.