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Department of Integrated Science and Engineering Computer Science Course
  • Utsunomiya Campus
Faculty of Science and EngineeringDepartment of Integrated Science and Engineering  Computer Science Course

Pioneering the next generation of information technology—educating
engineers who drive innovation and sustain our connected world.

Department of Integrated Science and Engineering, Computer Science Course Close-up

最先端の情報技術を活用できる力を身につける
情報技術、データサイエンス?AI、メディア表現のための技術を、これらの基礎となっている情報科学の諸理論から学ぶことができます。これにより、新しい技術へ対応できる力、技術を効果的に利活用する力とともに身につけます。

カリキュラム

In addition to programming, we also offer practical courses in which students can create their own AI and develop information systems in teams. Students will not only acquire technical skills, but also practical skills that will enable them to contribute to solving various social problems while working with others.

Syllabus

Department of Integrated Science and Engineering Computer Science Course Syllabus

Class Introduction

Programming related subjects
We have set up multiple programming courses that allow students to steadily acquire programming skills from introductory to practical levels. At the introductory level, the curriculum uses the programming language Python and allows students to learn from the basics. In addition, there are programming courses for object-oriented programming, which is essential for actual information system development, and for developing web applications, aiming to acquire programming skills that can immediately contribute to real work.

情報セキュリティ
安全な情報化社会を実現するための情報セキュリティについて、その理論的な側面から情報システムを利活用するうえでの考え方や仕組みについて学びます。暗号化技術や不正アクセス対策など情報セキュリティの考え方、認証技術など高度なコンピューターネットワークのセキュリティの実現に不可欠な技術や概念を学びます。

人工知能(AI)関連科目
情報科学の応用技術の一つである人工知能(Artificial Intelligence,AI)は、今まさに私たちの生活を大きく変えようとしています。情報科学コースでは、人工知能関連の科目を複数設置し、AIとはなにかといった基礎的な概念や理論を学ぶだけでなく、実際にAIを生成したりAIを組み込んだシステムを開発したりする演習を通して、AIの効果的な利活用のための実践的な力を身につけます。

Information Systems Related Subjects
There are several courses that teach the technologies and theories that are essential to realizing the information systems that support society, such as computer networks, databases, and information theory. In order to realize advanced DX (digital transformation) that utilizes these theories and technologies, theories and technologies for appropriately designing information systems and developing them efficiently and with high quality are also essential, and there are several practical courses to learn these.

Digital Media Content Production Seminar 1-4
One of the applied technologies in the field of information science is xR technology, such as three-dimensional computer graphics (3DCG), virtual reality (VR), and augmented reality (AR). These technologies are being used not only for digital media and content such as games, but also for social activities such as the metaverse and digital twins. In this class, you will learn techniques for creating applications and content that combine 3DCG and other digital media.

Computer Science Practice 1 & 2
This is a PBL (Project Based Learning) type practical class in which students work in teams to develop information systems. Just like in the actual development of information systems, students design, program, and complete the system themselves. Through this practical training, students also acquire generic skills such as the ability to identify problems, work in a team, and execute projects in a planned manner.

成績評価と単位認定

Grading Criteria

About our GPA System

The purpose of introducing the GPA (Grade Point Average) system is to 1. create a unified standard for the faculty, 2. create a standard with excellent fairness, and 3. create a standard that is internationally accepted, and to evaluate the results of learning with an objective numerical value called GPA. This system is roughly based on the grading system adopted by many universities overseas, and is an internationalized grading system that serves as an indicator of academic ability when studying abroad, advancing to Graduate School overseas, or finding employment at a foreign company.

Display of Grades and Assessment Criteria

Classification Grading Criteria GPA Grading Criteria Details of Assessment
Pass S. 4.0 90 percent or higher Represents particularly excellent grades.
A 3.0 80 percent Represents excellent grades
B. 2.0 70 percent Represents grades recognized as adequate.
C. 1.0 60 percent Represents the minimum grade acceptable as a pass.
Fail D. 0.0 59 points or less Represents that students have not reached the minimum grades acceptable as a pass
absence 0.0 Missing the exam Represents that students have not taken the exam for the class or have not submitted a report, etc.
Unqualified 0.0 Not eligible to take the exam Represents that students are not eligible to take the exam due to insufficient attendance at the class or have abandoned the course. 

GPA Calculation Method

GPA Calculation Method
  • *1 GPA will be rounded off to the third decimal place and expressed as a number with two decimal places.
  • *2 When a student retakes a failed course (fail, absent, or not qualified) and receives a pass grade, or when a student retakes a course and receives a fail grade (fail, absent, or not qualified), the grade before the retake is not included in the GPA. Qualification-related courses are excluded from the "total number of registered credits."
  • *3 It is desirable to have a GPA of 2.4 or higher (2.2 or higher for Department of Integrated Science and Engineering).

Credit Recognition

To earn credits

Credit system
University classes are taught on a credit system. The number of credits is determined based on the number of study hours, and one credit is set at 45 hours of study (of which class time is generally 15 to 45 hours) taking into account the teaching method, educational effect of the class, and necessary study outside of class time. For specific details, please refer to the number of credits listed in the "Course Table."

Earning credits
Credits can be earned by registering for classes at the beginning of each semester, attending classes, completing the necessary preparatory studies, and passing exams. University credits are based on the number of class hours. As a general rule, students must attend more than two-thirds of the class hours in order to be eligible to take exams. Please make attending classes your number one priority.

Number of credits required for graduation

To graduate, students must be enrolled for at least four years and earn at least 124 credits. The breakdown of the minimum number of credits required to graduate varies depending on the department, course, and year of enrollment.

Computer Science Course
In today's rapidly changing society, social issues tend to become more diverse and complex. Responding to these issues requires more than just knowledge from a single or limited field of expertise; it requires multifaceted thinking that combines the humanities and sciences. For this reason, liberal arts education courses are divided into four fields: humanities, social science, natural science, and a field that combines the humanities and sciences. Please study each field in accordance with the graduation requirements to acquire a multifaceted perspective.

Subject classification Number of units Remarks
General Education Liberal Arts Subjects Humanities-related fields 2 or more 8 or more Acquired 22 or more ※1
Social Sciences
Natural Sciences 2 or more
Interdisciplinary fields
First-year education subjects 2 or above (required)
Career-related courses 4 or above (required)
Information Education Subjects 2 or above (required)
Foreign Language Education 4 (Required)
Specialized courses Compulsory 47 Total 90 or more
Optional compulsory 10※2、8※2
Elective 25
Free Choice 12 General Education and specialized subjects
Excess and
Courses taken in other departments
total 124  
  • * Specialized subjects in other courses will be counted as specialized subjects minus elective subjects.
  • *1 Obtain 10 or more credits from five subject categories
  • *2Please refer to the course list for each course for details.

研究室

Students are studying a variety of research topics under the guidance of experienced faculty members.

Computer Science Course Laboratory