In the current society, it is essential in all fields to appropriately exploit "big data" for finding rules and/or making predictions/decisions. This course aims to help students to manipulate computer software tools for data analysis to get new findings.
Students will be able to understand the basis of data processing mechanisms and make use of various data analysis software tools appropriately.
classification, clustering, principal component analysis, dimension reduction, training/generalization errors, cross validation
|Intercultural skills||Communication skills||✔ Specialist skills||Critical thinking skills||✔ Practical and/or problem-solving skills|
In class, students are required to solve exercise problems that are linked with the contents of taught course ``XCO.T487 Fundamentals of data science".
|Course schedule||Required learning|
|Class 1||Prerequirement exam||Check basic knowledge about mathematics and Python language|
|Class 2||Arrangement of computing environment and warming-up of programming||Arrange computing environment and carry out simple excercises of programming|
|Class 3||Classification||Do exersises on methods for extracting discrimination rules from labeled data|
|Class 4||Clustering||Do exersises on methods for categorizing unlabeled data into several categories|
|Class 5||Principal component analysis||Do exersises on principal component analysis with mathematical issues related to it|
|Class 6||Dimension reduction||Do exersises on methods for dimension reduction such as multidimensional scaling and canonical correlation analysis|
|Class 7||Advanced topics||Do exersises on methods for ensemble learning|
|Class 8||General discussion||Discuss possible applications of data analysis in various fields|
Distributed via OCW-i
Based on reports for given assignments.
Take a prerequirement exam on "linear algebra", "analysis", and "basic grammar and functions of Python3" in the first class on Monday, December 2, 2019. Make sure to come to W531 or G115 no later than 15:05. Not allowed to take this course if you skip this exam, and may not be allowed depending on its score. It is also mandatory to take ``XCO.T487 Fundamentals of data science'' and "T490 Exercises in fundamentals in artificial intelligence" in parallel.
A prerequirement test is conducted in irregular class rooms W531 and G115 in the first class on Monday, December 2nd. Exercises are carried out using Google Colaboratory. Students are required to get Google accounts and to get ready for using functions of "file upload/download" in Google Drive.