School of Informatics and Data Science
|Subject Name in
|Informatics and data science, Exercise III
HIGAKI TORU,NAKASHIMA KENICHIRO,KOIKE MAYU,FURUKAWA YOSHIYA
|ヒガキ トオル,ナカシマ ケンイチロウ,コイケ マユ,フルカワ ヨシヤ
3rd-Year, Second Semester, 3Term
|Days, Periods, and Classrooms
(3T) Mon5-7：EDU K104,EDU K203,ENG 116
||Language of Instruction
Science and Technology
||College of Information Science, Information Science Department, 3rd grade
Image processing, generalized linear model, multivariate analysis, questionnaire survey
|Special Subject for Teacher Education
|・ Prerequisite subjects for "Image processing":|
Programming I, II, III, IV
Algorithms and data structures
Seminar on Information Data Science I "Data Structure and Algorithm"
・ Prerequisite subjects for "Survey Data Analysis 2":
Seminar on Information Data Science II "Survey Data Analysis 1"
Generalized linear model (GLM)
|Informatics and Data Science Program|
（Knowledge and Understanding）
・D1. Knowledge and skills required for understanding the theoretical system of statistics and data analysis, and for precisely and efficiently analyzing qualitative/quantitative information in big data.
（Abilities and Skills）
・A. Skills related to the development of an information infrastructure,information processing techniques, and technology for producing new added value through data analysis.
・ B. Ability to identify and solve new problems on their own by quantitative and logical thinking based on data, diverse perspectives, and advanced skills for information processing and analysis.
|In this class, students engage in exercises on specialized and practical content based on the knowledge that has been widely learned in previous lectures of the Faculty of Information Science. Students learn the ability to find solutions for given exercises and problems, to deal with them, and to summarize the results as reports in this class. Exercises will be conducted on the theme of "image processing" and "survey data analysis 2". All students engage in both themes through this class.
In "Image Processing", students will be needed to understand the basic algorithms for processing a large number of images by programming with Python. “Survey data analysis 2” is based on psychology and behaviormetrics. Students learn analysis such as generalized linear model and multivariate analysis, using the data collected in the theme survey data analysis 1 of Information and Data Science Exercise II.
guidance for the two themes, distribution for materials and notes.
Prepare for the themes.
Assign report tasks for each theme.
Conduct the final examination.
Theme "Image processing"
1,2: Create a program for using Python, reading, displaying, and drawing images.
3,4: Create a program for typical conversion of luminance and threshold processing of luminance value.
5,6: Create a representative filter processing program and process a large amount of image big data.
Theme "Survey Data Analysis 2"
1,2: Preparation for analysis plan from perspective of psychology and behaviormetrics.
3,4: Data processing.
5,6: Data analysis and discussion using generalized linear model.
|PC or AV used in
Use your personal computer. Bring it with you every time. Be fully charged.
|Learning techniques to be incorporated
|Review the knowledge that has been widely learned in previous lectures of the Faculty of Information Science.
||Submit report assignments for all the themes by the deadline.
||Comprehensively evaluate reports and regular examinations
|Summary of Practical Experience and Class Contents based on it
|Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.