日本語 English
| 開講年度/ Academic YearAcademic Year |
20242024 |
| 科目設置学部/ CollegeCollege |
人工知能科学研究科/Graduate School of Artificial Intelligence and ScienceGraduate School of Artificial Intelligence and Science |
| 科目コード等/ Course CodeCourse Code |
WR301/WR301WR301 |
| テーマ・サブタイトル等/ Theme・SubtitleTheme・Subtitle |
|
| 授業形態/ Class FormatClass Format |
ハイフレックス/HyFlexHyFlex |
| 授業形態（補足事項）/ Class Format (Supplementary Items)Class Format (Supplementary Items) |
|
| 授業形式/ Class StyleCampus |
講義/LectureLecture |
| 校地/ CampusCampus |
池袋/IkebukuroIkebukuro |
| 学期/ SemesterSemester |
春学期/Spring SemesterSpring Semester |
| 曜日時限・教室/ DayPeriod・RoomDayPeriod・Room |
|
| 単位/ CreditCredit |
22 |
| 科目ナンバリング/ Course NumberCourse Number |
AIR7100 |
| 使用言語/ LanguageLanguage |
日本語/JapaneseJapanese |
| 履修登録方法/ Class Registration MethodClass Registration Method |
科目コード登録/Course Code RegistrationCourse Code Registration |
| 配当年次/ Grade (Year) RequiredGrade (Year) Required |
配当年次は開講学部のR Guideに掲載している科目表で確認してください。配当年次は開講学部のR Guideに掲載している科目表で確認してください。 |
| 先修規定/ prerequisite regulationsprerequisite regulations |
|
| 他学部履修可否/ Acceptance of Other CollegesAcceptance of Other Colleges |
履修登録システムの『他学部・他研究科履修不許可科目一覧』で確認してください。 |
| 履修中止可否/ course cancellationcourse cancellation |
－（履修中止制度なし/ No system for cancellation) |
| オンライン授業60単位制限対象科目/ Online Classes Subject to 60-Credit Upper LimitOnline Classes Subject to 60-Credit Upper Limit |
|
| 学位授与方針との関連/ Relationship with Degree PolicyRelationship with Degree Policy |
各授業科目は、学部・研究科の定める学位授与方針（DP）や教育課程編成の方針（CP）に基づき、カリキュラム上に配置されています。詳細はカリキュラム・マップで確認することができます。 |
| 備考/ NotesNotes |
|
| テキスト用コード/ Text CodeText Code |
WR301 |
By experiencing the characteristics, significance, and appeal of each field of artificial intelligence science, you will understand the research methods and diversity in each field, increase your interest in artificial intelligence science research, and grasp the overall picture of artificial intelligence science.
Multiple faculty members from diverse fields will give lectures on cutting-edge knowledge, research issues, and research trends in their respective research areas. Participants will discuss and exchange opinions on commonalities and differences in research methods in light of their own areas of expertise. By being exposed to diverse perspectives and ways of thinking, students can reconsider their field of expertise from a broader perspective and multiple angles, deepen their understanding of specialized knowledge, and develop interdisciplinary thinking skills. By cultivating a broad perspective and thinking ability in artificial intelligence science, students will acquire the ability to tackle the diverse and complex research challenges they will face after completing their doctoral program.
※Please refer to Japanese Page for details including evaluations, textbooks and others.
人工知能科学の諸領域各の特色、意義、魅力に触れることで、各領域における研究方法とその多様性を理解し、人工知能科学研究に対する興味・関心を高め、人工知能科学の全体像を把握する。
By experiencing the characteristics, significance, and appeal of each field of artificial intelligence science, you will understand the research methods and diversity in each field, increase your interest in artificial intelligence science research, and grasp the overall picture of artificial intelligence science.
多様な分野の複数の教員がそれぞれの研究領域における先端知識、研究課題、研究動向について講義を行う。受講者自身の専門領域に照らし合わせ、研究方法の共通点・相違点について議論・意見交換を行う。多様なものの見方・考え方に触れることで自身の専門領域を広い視点から多角的に捉え直し、専門知識の理解度を深め、学際的思考力を養う。人工知能科学の幅広い視野と思考力を培うことで、博士課程修了後に直面するであろう多種多様で複雑な研究課題に取り組むことのできる力を身につける。
Multiple faculty members from diverse fields will give lectures on cutting-edge knowledge, research issues, and research trends in their respective research areas. Participants will discuss and exchange opinions on commonalities and differences in research methods in light of their own areas of expertise. By being exposed to diverse perspectives and ways of thinking, students can reconsider their field of expertise from a broader perspective and multiple angles, deepen their understanding of specialized knowledge, and develop interdisciplinary thinking skills. By cultivating a broad perspective and thinking ability in artificial intelligence science, students will acquire the ability to tackle the diverse and complex research challenges they will face after completing their doctoral program.
| 1 | 人工知能とデータサイエンス |
| 2 | 人工知能とデータサイエンス |
| 3 | 人工知能とデータサイエンス |
| 4 | 人工知能とデータサイエンス |
| 5 | 人工知能とデータサイエンス |
| 6 | 人工知能とデータサイエンス |
| 7 | 人工知能とデータサイエンス |
| 8 | 人工知能の応用と社会実装 |
| 9 | 人工知能の応用と社会実装 |
| 10 | 人工知能の応用と社会実装 |
| 11 | 人工知能の応用と社会実装 |
| 12 | 人工知能の応用と社会実装 |
| 13 | 人工知能の応用と社会実装 |
| 14 | 人工知能の応用と社会実装 |
板書 /Writing on the Board
スライド（パワーポイント等）の使用 /Slides (PowerPoint, etc.)
上記以外の視聴覚教材の使用 /Audiovisual Materials Other than Those Listed Above
個人発表 /Individual Presentations
グループ発表 /Group Presentations
ディスカッション・ディベート /Discussion/Debate
実技・実習・実験 /Practicum/Experiments/Practical Training
学内の教室外施設の利用 /Use of On-Campus Facilities Outside the Classroom
校外実習・フィールドワーク /Field Work
上記いずれも用いない予定 /None of the above
授業中に参考文献としてあげられた論文を読むこと
| 種類 (Kind) | 割合 (%) | 基準 (Criteria) |
|---|---|---|
| 平常点 (In-class Points) | 100 |
随時に出題される小レポート(100%) |
| 備考 (Notes) | ||
なし/None