▶Japanese
Post to SNS
- Home
- > School of Environment and Society
- > Graduate major in Technology and Innovation Management
- > Methodology of Mathematical and Computational Analysis I
- School of Science
-
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
- Graduate major in Technology and Innovation Management
- Instructor(s)
- Kajikawa Yuya Nakamaru Mayuko
- Class Format
- Lecture / Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Sat9-10(CIC913)
- Group
- -
- Course number
- TIM.A405
- Credits
- 1
- Academic year
- 2016
- Offered quarter
- 1Q
- Syllabus updated
- 2016/12/14
- Lecture notes updated
- 2016/5/6
- Language used
- Japanese
- Access Index
-
Lecture
Lecture 1 Learning Data Science
2016.4.9(Sat.) 9-10Session
Lecture
Lecture 2 Statistical Analysis
2016.4.16(Sat.) 9-10Session
Lecture
Lecture 3 Machine Learning
2016.4.23(Sat.) 9-10Session
Lecture
Lecture 4 Non-structured Data Analysis
2016.4.30(Sat.) 9-10Session
Lecture
Lecture 5 Statistical Analysis Practice
2016.5.7(Sat.) 9-10Session
Lecture
Lecture 6 Machine Learning Practice
2016.5.14(Sat.) 9-10Session
Lecture
Lecture 7 Pragmatic Data Analysis in Business
2016.5.28(Sat.) 9-10Session
Lecture
Lecture 8 Reflection
2016.6.4(Sat.) 9-10Session
It is necessary for those who refer to the PDF file to use "Adobe Reader" as the plug-in software of Adobe System Company.
If you don't have the software, please download from this item (free).
