2025 (Current Year) Faculty Courses School of Environment and Society Undergraduate major in Civil and Environmental Engineering
Computers and Fundamental Programming B
- Academic unit or major
- Undergraduate major in Civil and Environmental Engineering
- Instructor(s)
- Hitomu Kotani / Ayako Akutsu
- Class Format
- Lecture/Exercise (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Tue
- Class
- -
- Course Code
- CVE.M303
- Number of credits
- 0.50.50
- Course offered
- 2025
- Offered quarter
- 2Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
Numerical analysis using computer is now important and essential skill for various fields. In this class, computer language Fortran 90/95, which is especially used in large-scale numerical computing, is used. By understanding basic grammar of the computer language and algorithms of major numerical-analysis methods, which are commonly used in research fields, basic programing skill will be acquired.
Through this course, students who don’t have any programming experience are expected to understand algorithms of major numerical-analysis methods and to be able to make basic program for numerical analysis.
Course description and aims
By the end of this class, students will be able to:
(1) understand basic grammars for programming
(2) understand algorithms of major numerical analysis methods required in research and development
(3) write basic programs for numerical analysis of phenomena according to their own needs, and
(4) understand and implement the basic concepts and algorithms of optimization (linear and nonlinear programming) and statistical inference (resampling, etc.) and be able to deal with specific problems
Keywords
numerical analysis, algorithm, Fortran, programming, numerical optimization, statistical inference
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Basics of programming and algorithms is trained through both lectures and exercises with using terminal of GSIC.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Lecture: Theory of linear programming | Understand algorithms of linear programming. |
| Class 2 | Exercise: Implementation of linear programming | Implement algorithms of linear programming. |
| Class 3 | Lecture: Theory of nonlinear programming | Understand algorithms of nonlinear programming. |
| Class 4 | Exercise: Implementation of nonlinear programming | Implement algorithms of nonlinear programming. |
| Class 5 | Lecture: Theory of statistical inference | Understand algorithms of statistical inference. |
| Class 6 | Exercise: Implementation of statistical inference | Implement algorithms of statistical inference. |
| Class 7 | Project and Q&A | Programming for the final project and Q&A etc. |
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)
Noting
Reference books, course materials, etc.
Handouts will be distributed before the beginning of class via T2SCHOLA.
Following textbook is recommended but will not be used in the course:
金谷 健一：これなら分かる最適化数学: 基礎原理から計算手法まで、共立出版、2005
小西 貞則・越智 義道・大森 裕浩：計算統計学の方法―ブートストラップ・EMアルゴリズム・MCMC (シリーズ予測と発見の科学 5)、朝倉書店、2008
Evaluation methods and criteria
Learning achievement is evaluated by combining results from reports.
Related courses
- CVE.M301 ： Computers and Fundamental Programming A
- CVE.M302 ： Computers and Applied Programming
Prerequisites
Completing CVE.M301 or same level as CVE.M301 are strongly recommended.
Lectures and exercises will be conducted using the educational computer system of the University, though students may also install the computing environment on their own PCs. However, if the course is to be held online due to the reemergence of the COVID-19 or other reasons, students will have no choice but to use their own PCs for the exercises. Under such circumstances, students must own a PC with an OS such as Windows, MacOS, Linux, etc. to be able to take the course.