National Taiwan University

This introductory semiconductor course is specifically designed for interdisciplinary learners. Leveraging professors from STEM (engineering, science, engineering, electrical engineering, and computer science) backgrounds, the course utilizes unit-based thematic teaching to help students understand semiconductor terminology, principles, and forward-looking applications, while also developing their ability to plan for further learning. The course features a holistic overview and does not emphasize related mathematical theories; therefore, it also serves as a general introductory course in contemporary materials science, suitable for students of all backgrounds and academic levels (including graduate students) interested in semiconductor technology. As an introductory course for interdisciplinary learners, this course first provides an overview of the current semiconductor world and how self-learners can modularly understand semiconductor technology. It then explores forward-looking chip applications and AI development to help students understand the importance of semiconductors for future societal development and even human civilization, and why undergraduate and graduate students should study semiconductor general knowledge. The course then progresses through basic solid-state physics and chemistry, materials and components, process equipment, and smart manufacturing modules, concluding with a comprehensive reflection on chip globalization and AI development. There are no exams for this course. Students  integrate the knowledge they have acquired and explore a personalized learning map by submitting handwritten study notes, group discussion assignments, and final forum poster activities.

This course equips students with a various set of analytical skills, computational tools, and research methodologies essential for producing high-quality research in Finance, Management, and Economics. It emphasizes the principles and practices required to conduct rigorous and impactful research, focusing on methods and real-world applications. Unlike traditional courses that provide a broad overview of knowledge, this course dives deeper into selected advanced topics, prioritizing research design and practical implementation. The curriculum introduces cutting-edge methodologies, including but not limited to: Macroeconomics, Continuous-time dynamic contracting problems, Computational methods in economics, Game theory applications in Finance, Causal machine learning, and Regression discontinuity and kink design. A key focus of the course is on the practical application of these methodologies and the development of skills necessary for writing academic research papers. Students receive guidance on crafting a high-quality term paper and are required to use LaTeX for their submissions. By the end of the course, students have the tools and knowledge to conduct empirical research independently and the ability to write and present a scientific paper to a professional standard.

This course focuses on discussing the changes in the "daily life experiences" of ordinary people within the People's Republic of China and the corresponding historical development and writing strategies. The focus is on re-examining the historical development of the People's Republic of China from the perspective of "ordinary people".

This course introduces the main concepts and theories of classroom management. It begins with an educational philosophy perspective to help prospective teachers reflect on the essential meaning of classroom management. This course helps establish a concept of classroom management, so as to benefit students when dealing with the issues arising from the interactions between teachers, students and parents that they will directly face in the teaching field. In the "Teacher Professional Development Assessment" currently implemented by the Ministry of Education in primary and secondary schools, classroom management indicators account for a significant proportion (6-1. Creating a positive and interactive classroom atmosphere, 6-2. Creating a safe and conducive learning environment, 6-3. Establishing classroom routines that facilitate student learning, etc.). Each sub-indicator emphasizes classroom vision, routines, cohesion, positive communication, learning environment, handling unexpected events, and the ability to provide respectful and differentiated guidance.

This course is a survey of the main ideas and techniques of game-theoretic analysis related to business decisions. As such, the course emphasizes the identification and analysis of archetypal strategic situations frequently occurring in business situations. The course has a strong experiential component. Students repeatedly participate in a variety of strategic situations thereby developing the ability to translate their analyses into practice. A working knowledge of basic calculus and ease with algebraic manipulation are prerequisites of the course. Prior exposure to microeconomics is very helpful.

Machine learning is a fast-growing field and plays a central role in the era of AI and big data with many applications in prediction and data analysis. In particular, optimization formulations and algorithms are key to analysis and design of efficient methods in machine learning problems. This course focuses on the optimization models arising from various machine learning problems and introduce efficient algorithms for solving these models. The course covers basic convex analysis, model formulation, and fundamental (stochastic) first-order methods, supplemented with recent developments in the related literature.

This course will analyze media content in several different medium, such as photographs, newspaper articles, advertisements, tv shows, movies, new media, public relations, fake news and digital literacy. It helps develop an understanding of how this media content influences people in everyday life, social development and political economic changes. It defines Information Literacy are the skill set needed to locate and recognize quality information resources to help students utilize the information in a responsible and effective way and defines Media Literacy as a way of thinking about the media and a way of deconstructing and understanding media messages to gain more control over them. Other topics include Resource Literacy, Social-Structural Literacy, Research Literacy, and Publishing Literacy.

This course begins with an overview of the definition of personality and the primary research methods used in personality psychology. It systematically introduces major theoretical perspectives, including psychoanalytic approaches, phenomenological and humanistic theories, trait theories, and contemporary social-cognitive, cultural, and neurobiological perspectives. Across different course units, the instructor incorporates recent data science and neuroscience research related to personality, drawing in part from the instructor’s own ongoing work in these areas. In the research project component, students engage in collaborative interactions with AI tools (LLMs). Through this process, students not only learn how to use AI to deepen their understanding of theoretical frameworks, but also enhance their creativity and competence in applying personality theories to empirical research.

This course introduces the creative and mysterious world of the venture capital (VC) and private equity(PE) investments. This course brings in the latest and most used VC/PE investment methodologies and practical tools from Silicon Valley, the heart of the global VC/PE industry. It starts with investigating the overall ecosystem and relationship between start-ups, VC’s, and Fund of Funds. Then it picks up the practical tools on the legal framework, organizational structures, funding channels and types, pre and post-money valuation methodologies, and pipeline generation. The course takes a deep dive into the exiting strategies including M&A, roadshow preparation, IPO, (Leveraged) Buyout, secondary market sales, and final LP/GP distributions. Throughout the course, students track the current start ups and VC/PE funding rounds as they happen and cross-reference these real life deals with the tools and methodologies delivered in this course.

This course begins with an introduction to the evolution of computers and their operating principles. It then gradually guides students to become familiar with programming structures and application design processes, including: basic syntax, flow control, exception handling, input/output, and classes. The course topics are as follows: Introduction Python Basics Flow Control Functions Sequence, Dictionary, and Set Array-Oriented Programming with NumPy File, and Exception Object-Oriented Programming.