Please check the grading scale that applies to this course. If the Course Code ends without “- P/F”, this is a course with a letter grade (A+, A, B, C, F). If the Course Code ends with “-P/F”, this is a Pass/Fail Course The later Wittgenstein’s views about language and meaning, especially as presented in Philosophical Investigations, are among the most important arguments in twentieth century philosophy, exerting great influence not only over traditional philosophy, but also a diverse and widespread range of fields in the humanities, social sciences, and cognitive science. This course will focus on Wittgenstein’s transition from the theory of language as a logical picture of reality outlined in the Tractatus, still in essence a dominant view of language, to his later understanding of language and meaning in terms of language’s use in social “language games”. The three most significant arguments for the development of this general view in Philosophical Investigations will be studied: meaning as use; considerations about rule following and the consequences for intentionality and representation; the impossibility of a private language. A general understanding of the later Wittgenstein’s anti-theoretical philosophical method will emerge along with an understanding of the relevance of the later Wittgenstein for current philosophical questions about language.

Please check the grading scale that applies to this course. If the Course Code ends without “-P/F”, this is a course with a letter grade (A+, A, B, C, F). If the Course Code ends with “-P/F”, this is a Pass/Fail Course The later Wittgenstein’s views about language and meaning, especially as presented in Philosophical Investigations, are among the most important arguments in twentieth century philosophy, exerting great influence not only over traditional philosophy, but also a diverse and widespread range of fields in the humanities, social sciences, and cognitive science. This course will focus on Wittgenstein’s transition from the theory of language as a logical picture of reality outlined in the Tractatus, still in essence a dominant view of language, to his later understanding of language and meaning in terms of language’s use in social “language games”. The three most significant arguments for the development of this general view in Philosophical Investigations will be studied: meaning as use; considerations about rule following and the consequences for intentionality and representation; the impossibility of a private language. A general understanding of the later Wittgenstein’s anti-theoretical philosophical method will emerge along with an understanding of the relevance of the later Wittgenstein for current philosophical questions about language.

At the end of the course, the student should have familiarised with the key concepts informing epistemological and methodological debates in social science, such as hypothesis, theory, falsification, verification, covering law, causality, with particular consideration for positivistic paradigms and anti- or post-positivistic reactions. The student should be aware of the specific difficulties of social scientific disciplines in studying human societies arising from the problematic separation between the studied object and the studying subject, and the link between social science and the political dimension. He should familiarise with problems of social research design, starting from the specificities characterizing the various stages of social science research. The student should become aware of the functional classification of social science methods in qualitative and quantitative, familiarising with a number of techniques in both domains, while grasping that contemporary social research increasingly requires the application of different methods and interdisciplinary approaches, which also lead to the necessity of teamwork coordination. The course also aims at providing a large variety of examples where the concepts and principles described above find their application and didactic clarification. Those examples will focus in particular on the study of technology and its social impact. Finally, the student should become aware of the moral implications, limits and rules informing social science research, as well as of the role and importance of effective communication in the social sciences.

This course confronts philosophy's most profound questions about the human condition with data-driven insights from modern behavioral science. For millennia, philosophers have used reason and introspection to ask: What is knowledge? What does it mean to be moral? What is love and happiness? How to deal with human violence? How to be free? What is the self? In this class, we will place these classical debates about the human nature/condition in direct conversation with cognitive psychology, behavioral economics, and social/evolutionary psychology. We will explore how far science can answer philosophical questions. <<Learning Goals>> - Identify and articulate key classical philosophical problems in epistemology (knowledge), ethics (morality), and metaphysics (self, love, free will). - Explain core concepts from behavioral science, such as dual-process theory, cognitive biases, moral foundations theory, and affective forecasting, while reasoning about major philosophical inquiries. - Analyze how empirical findings from behavioral science challenge, support, or reframe traditional philosophical arguments. - Critically Evaluate the limits of both "armchair" philosophical reasoning and purely descriptive scientific data in addressing normative ("ought") questions. - Synthesize insights from both fields to develop more nuanced and empirically-grounded positions on complex human issues.

Statistics and biometrics have emerged as crucial disciplines not only in agricultural sciences but also in various other fields. This significance is primarily attributed to three factors: Firstly, advancements in data measurement techniques have facilitated the collection of extensive and diverse biological and agronomic data that were previously unattainable. Secondly, the evolution of data science methodologies has enabled the integration and modeling of such collected data. Thirdly, the enhancement of computational capabilities has empowered the utilization of these methodologies. These advancements have rendered statistical and biometric methods indispensable for extracting insights from the vast and varied biological and agronomic datasets. Throughout this lecture series, a diverse array of biological and agronomic datasets will serve as illustrative examples to demonstrate various analytical methods. Delivered in a hands-on format, utilizing R, Python, and Matlab, the aim is to equip students with practical analysis skills. The initial portion of the course, spanning the first one-third, will focus primarily on techniques for summarizing, visualizing, and modeling relationships within multivariate datasets. In the subsequent one-third, students will delve into linear models, linear mixed models, local regression, and nonlinear models. Finally, in the last segment, students will explore image analysis, machine learning, and deep learning methods. While the course will cover a broad spectrum of methods, ranging from introductory to advanced levels, the emphasis will be on developing the capability to independently conduct analyses rather than on elaborating on the theoretical underpinnings of the methods.

The course will take an intersectional approach to why we commonly find an underrepresentation of women in the "science" fields. The course will begin by addressing our own unconscious biases and stereotypes, and question the research behind male and female differences. We will cover the brief history of the underrepresentation of minorities and explore research articles on why and how women and other minorities have been excluded from STEM fields. We will primarily discuss how representation and the sense of belonging are important for diversity in the sciences to flourish. Students will be expected to read scientific articles, discuss them in class, and apply those concepts to examine their own social environments.

The course will take an intersectional approach to why we commonly find an underrepresentation of women in the “science” fields. The course will begin by addressing our own unconscious biases and stereotypes and question the research behind male and female differences. We will cover the brief history of the underrepresentation of minorities and explore research articles on why and how women and other minorities have been excluded from STEM fields. We will primarily discuss how representation and the sense of belonging are important for diversity in the sciences to flourish. Students will be expected to read scientific articles, discuss them in class, and apply those concepts to examine their own social environments.

Students will explore and debate questions about human experience from multiple perspectives as they discover influential works from cultures around the world, both ancient and modern. Students will develop critical approaches and analytical skills as they exchange ideas with peers, ask questions, and respond to works in different genres through a variety of expressive modes. The course will focus on four fundamental themes: love, identity, death, and the meaning of life.

Students will explore and debate questions about human experience from multiple perspectives as they discover influential works from cultures around the world, both ancient and modern. Students will develop critical approaches and analytical skills as they exchange ideas with peers, ask questions, and respond to works in different genres through a variety of expressive modes. The course will focus on four fundamental themes: love, identity, death, and the meaning of life.

広く産学官にわたってグローバルに活躍するために必要な「俯瞰力」を養成することを目指す。物質科学の各分野について最先端の知識を修得し、自分の専門分野と周辺分野がどのように関連するか、あるいはし得るか、について深く考察するために、第一線で活躍する講師の方々にその分野の最前線を概観していただく。さらに、それらの講義を通して異分野間のコミュニケーションを円滑に進めるための具体的方法論を学ぶ。 This survey course is designed to enable students to develop the broad perspective that is required of global leaders working in and across industry, academia, and government. Students will gain knowledge and insight on advancements in each field of materials science research, given by leading researchers working on the frontline in those fields. This will allow students to consider how peripheral fields are related to their own area of expertise, and to consider the potential for forging bridges between related fields in the future. In addition, students will learn specific methodologies designed to facilitate smooth communication among different disciplines.