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
✔ Specialist skills | Intercultural skills | Communication 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.T677
Fundamentals of progressive 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 exercises of programming |
Class 3 | Classification | Do exercises on methods for extracting discrimination rules from labeled data |
Class 4 | Principal component analysis | Do exercises on principal component analysis with mathematical issues related to it |
Class 5 | Clustering | Do exercises on methods for categorizing unlabeled data into several categories |
Class 6 | Dimension reduction | Do exercises on methods for dimension reduction such as multidimensional scaling and canonical correlation analysis |
Class 7 | Ensemble learning | Do exercises on methods for ensemble learning |
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
None
Based on reports for given assignments.
Based on reports for given assignments.
Only doctor course students can register this exercise.
When you apply this exercise, take "XCO.T677 Fundamentals of progressive data science'' , "XCO.T679 Fundamentals of progressive artificial Intelligence" and "T680 Exercises in fundamentals in progressive artificial intelligence" of the same quarter of the same year in parallel. If there are many applicants, a lottery may be held.
Exercises are carried out using Google Colaboratory. Students are required to get Google accounts and to get ready for usingfunctions of "fi le upload/download" in Google Drive.