2025 (Current Year) Faculty Courses School of Computing First-Year Courses
Foundations of Computing 3
- Academic unit or major
- First-Year Courses
- Instructor(s)
- Naoto Miyoshi / Takafumi Kanamori / Zin Arai / Shunsuke Tsuchioka
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Thu (M-178(H1101))
- Class
- -
- Course Code
- XCO.B103
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Oct 20, 2025
- Language
- Japanese
Syllabus
Course overview and goals
Understand the basics of network, topology, statistics, probability, etc., which are part of the curriculum of the Department of Mathematical and Computing Science. In these fields, we construct mathematical models that extract only the essence of real problems, and develop mathematical and probability theories that are conscious of algorithms that implement this model on a computer. Among them, the explanation will focus on themes that do not use much specialized background knowledge.
Course description and aims
Understand the basics of network, topology, differential equations, statistics, probability, etc., which are part of the curriculum of the Department of Mathematical and Computing Science.
Keywords
network, topology, statistics, probability
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Multiple faculty members will give lectures on each topic in omnibus format.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Discrete probability |
Learn the probability on discrete space and its applications. |
| Class 2 | Discrete random variables and expectations |
Learn discrete-valued random variables and their applications. |
| Class 3 | Statistics in the Era of the Reproducibility Crisis |
In light of the reproducibility crisis in scientific research, this lecture introduces basic approaches to handling data and gives an overview of statistical literacy. Short quizzes will be given through the LMS during the lecture, so please bring a PC or other device. |
| Class 4 | Network, Topology, and their Applications (1/2) |
Learn the mathematical basics of network, topology, and their applications. |
| Class 5 | Network, Topology, and their Applications (2/2) |
Learn the mathematical basics of network, topology, and their applications. |
| Class 6 | Experimental Mathematics (1/2) |
Learn experimental mathematics. |
| Class 7 | Experimental Mathematics (2/2) |
Learn experimental mathematics. |
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)
Depends on each lecturer.
Reference books, course materials, etc.
Depends on each lecturer.
Evaluation methods and criteria
Reports, quizzes, etc.
Related courses
- XCO.B101 ： Foundations of Computing 1
- XCO.B102 ： Foundations of Computing 2
Prerequisites
No requirements.