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School of Engineering
- Undergraduate major in Mechanical Engineering
- Undergraduate major in Systems and Control Engineering
- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
- Undergraduate major in Industrial Engineering and Economics
- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 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
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
-
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 Systems and Control Engineering
- Instructor(s)
- Hasegawa Osamu
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Tue7-8(S515) Fri7-8(S515)
- Group
- -
- Course number
- SCE.S302
- Credits
- 2
- Academic year
- 2016
- Offered quarter
- 3Q
- Syllabus updated
- 2016/4/27
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course provides students with a wide range of skills of basic mathematical science that is necessary to system design and control.
Student learning outcomes
At the end of this course, students will be able to understand the basics of various mechanisms behind systems,
And furthermore, lay the groundwork for the expertize acquisition.
Keywords
Machine Learning, Artificial Intelligence, Complex Systems, Intelligent Systems, Intelligent Robots
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | ✔ Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
Dr Hasegawa will give lectures in the first half of the academic year, after that, some supervisors who are conducting advanced research in the field of computational intelligence and systems science will give lectures about systems and mathematical science form diverse perspectives.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Learner and learning methods | Write reports about learning machines. |
| Class 2 | Basics of the Bayes theory | Write reports about bayes theory. |
| Class 3 | Probabilistic models and discriminant functions | Write reports about mathematical models. |
| Class 4 | Basics of neural networks | Write reports about neural networks. |
| Class 5 | Time series data analysis | Data analysis/analyses, practice |
| Class 6 | Image data analysis | Image processing, practice |
| Class 7 | Multi-modal data analysis | Write reports about intelligent robots. |
| Class 8 | Agent systems | Homework specified by the instructor. |
| Class 9 | Knowledge systems | Homework specified by the instructor. |
| Class 10 | Complex networks | Homework specified by the instructor. |
| Class 11 | Intelligent interactive systems | Homework specified by the instructor. |
| Class 12 | Self organizing systems | Homework specified by the instructor. |
| Class 13 | Evolutionary systems | Homework specified by the instructor. |
| Class 14 | System biology | Homework specified by the instructor. |
| Class 15 | Molecular robotics | Homework specified by the instructor. |
Textbook(s)
Text book specified by the instructor.
Reference books, course materials, etc.
All materials used in class can be found on OCW-i.
Assessment criteria and methods
Students' course scores are based on homework and final exams.
Related courses
- ZUS.I301 ： Introduction to Artificial Intelligence
- ICT.H318 ： Foundations of Artificial Intelligence (ICT)
- CSC.T272 ： Artificial Intelligence
- ART.T548 ： Advanced Artificial Intelligence
Prerequisites (i.e., required knowledge, skills, courses, etc.)
No prerequisites.
Other
Lectures in second-half are subject to variation.
