GBP (Global Business Program)

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PRI200LA(情報学基礎 / Principles of informatics 200)
Information Technology

Yuko MATSUDA

Class code etc
Faculty/Graduate school GBP (Global Business Program)
Attached documents
Year 2022
Class code P0163
Previous Class code
Previous Class title
Term 春学期授業/Spring
Day/Period 木3/Thu.3
Class Type
Campus 市ヶ谷
Classroom name 各学部・研究科等の時間割等で確認
Grade 1~4
Credit(s) 2
Notes ※Only a certain number of students
Open Program
Open Program (Notes)
Global Open Program
Interdepartmental class taking system for Academic Achievers
Interdepartmental class taking system for Academic Achievers (Notes)
Class taught by instructors with practical experience
SDGs CP
Urban Design CP
Diversity CP
Learning for the Future CP
Carbon Neutral CP
Chiyoda Campus Consortium
Category 基礎科目/Liberal Arts Courses
情報学分野/Information Technology
リベラルアーツ科目/Upper Division Liberal Arts Courses

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Outline and objectives

You will learn the information and communication technology with Python programming.

Goal

You will understand the essence of the current popular IT topics including the Internet, computer system, data science and the artificial intelligence.

Default language used in class

英語 / English

Method(s)(学期の途中で変更になる場合には、別途提示します。 /If the Method(s) is changed, we will announce the details of any changes. )

The class materials will be available in the online notebooks. Teaching style is basically face-to-face, however simply applicable to the online style due to the online notebooks. Each class is taught in the text mixed with programs and assign a short homework.

Active learning in class (Group discussion, Debate.etc.)

あり / Yes

Fieldwork in class

なし / No

Schedule

授業形態/methods of teaching:対面/face to face

※各回の授業形態は予定です。教員の指示に従ってください。

1[対面/face to face]:Python Programming

You will learn to be able to read Python code.

2[対面/face to face]:Computer System and the Internet

You will understand how computer works and the Internet works.

3[対面/face to face]:Data Encoding

Computed data including characters should be converted to machine readable code.

4[対面/face to face]:Data Science [1]

You will learn DataFrame. Python based data handling tool DataFrame performs Excel like actions and more.

5[対面/face to face]:Data Science [2]

You understand the trend with data viewing.

6[対面/face to face]:Data Science [3]

You will learn how to draw map.

7[対面/face to face]:Data Science [4]

You will learn how to plot data on the map.

8[対面/face to face]:Machine Learning [1]

You will learn how to predict with linear regression.

9[対面/face to face]:Machine Learning [2]

You will learn how to predict with k-nearest neighborhood.

10[対面/face to face]:Machine Learning [3]

Big example: MNIST. You will learn how to classify hand written digits.

11[対面/face to face]:Machine Learning [4]

You will learn how to classify hand written digits with Perceptron.

12[対面/face to face]:Information Encoding [1]

Encryption.

13[対面/face to face]:Information Encoding [2]

Credit Card/Bar Code/QR code

14[対面/face to face]:Summary

You are given the review of the whole classes.

Work to be done outside of class (preparation, etc.)

No special work will be assigned to you. However you need to finish all the homework assigned in the class. Preparatory study and review time for this class are 2 hours each.

Textbooks

None.

References

All texts are uploaded in HOPPII.

Grading criteria

To pass the study quality and to get the grade, you need attend the whole classes and submit all the homeworks. The quality of the last homework will dominate 80% of the score and the 20% of the score depends on homeworks issued on every classes. You need get more than 60 points for the total 100 points to pass this class.

Changes following student comments

None.

Equipment student needs to prepare

none.

Others

My career introduction. I have been designing, implementing automatic programming and teaching human knowledge into computer, especially in natural language.