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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
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- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Transdisciplinary Science and Engineering
- Instructor(s)
- Yamashita Yukihiko Akita Daisuke
- Class Format
- Lecture / Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Tue1-4(学術国際情報センター3F第1実習室)
- Group
- -
- Course number
- TSE.A324
- Credits
- 2
- Academic year
- 2018
- Offered quarter
- 4Q
- Syllabus updated
- 2018/10/11
- Lecture notes updated
- -
- Language used
- English
- Access Index
-
Course description and aims
The purposes of the first half of this class are to learn a basic programming technique of Python and to be able to make programs for numerical analysis by succeeding "Programming and numerical analysis". Students learn from basic grammar of Python to data structures such as list and array. And students learn algorithms of statistical processing and signal and image processing, and practice programmings.
The purpose of the second half of this class is to develop practical abilities such as applied numerical simulation methods, visualization of results by succeeding "Programming and numerical analysis". In the group work, students will experience not only numerical simulation or programming but also problem setting, modeling, and evaluation of results.
Student learning outcomes
Students can obtain the following abilities by this lecture
(1) Basic grammar of Python
(2) Algorithms of statistical processing and signal and image processing
(3) Basic programming
Keywords
Programming,numerical analysis, algorithm, Python, statistical processing, signal and image processing, modeling, visualization
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
In the beginning part of each class, students learn about grammar of a programming language and algorithms. After that, make programs based on them.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Basic grammar and control of Python | Be able to make simple programs of Python with branch and loops. |
| Class 2 | Basic data structure and sort | Be able to make programs of Python with list and array to sort them. |
| Class 3 | Statistical processing | Be able to make programs of Python to calculate average and variance from data and perform a statistical test. |
| Class 4 | Signal and image processing | Be able to make programs of Python for DFT and signal and image processing. |
| Class 5 | Visualization of results and 3D modeling using Paraview, Newtonian flow simulation | Be able to visualize results using Paraview |
| Class 6 | Review of simultaneous equation and solving method of elliptic partial differential equation | Be able to make a program to solve elliptic partial differential equations |
| Class 7 | Group work | Prepare for the group presentation |
| Class 8 | Group presentation | Group presentation |
Textbook(s)
None
Reference books, course materials, etc.
John V. Guttag, "Introduction to Computation and Programming Using Python," MIT Press, 2013.
Assessment criteria and methods
Learn programming and be able to make programs by using algorithms of numerical analysis.
Practices and reports (100%)
Related courses
- TSE.A307 ： Programming and numerical analysis
Prerequisites (i.e., required knowledge, skills, courses, etc.)
None
