Vorlesungsverzeichnis
Suchen Sie hier über ein Suchformular im Vorlesungsverzeichnis der Leuphana.
Veranstaltungen von Qianxun Chen
Lehrveranstaltungen
As We May Speak: From NLP to Chatbot (Seminar)
Dozent/in: Qianxun Chen
Termin:
Einzeltermin | Do, 23.10.2025, 14:00 - Do, 23.10.2025, 17:30 | HMS 210
Einzeltermin | Do, 06.11.2025, 14:00 - Do, 06.11.2025, 17:30 | HMS E08
Einzeltermin | Sa, 15.11.2025, 10:00 - Sa, 15.11.2025, 16:00 | HMS 139
Einzeltermin | Do, 20.11.2025, 14:00 - Do, 20.11.2025, 17:30 | HMS 205
Einzeltermin | Do, 04.12.2025, 14:00 - Do, 04.12.2025, 17:30 | C 7.319 Seminarraum
Einzeltermin | Sa, 13.12.2025, 10:00 - Sa, 13.12.2025, 16:00 | HMS 139
14-täglich | Donnerstag | 14:00 - 17:30 | 18.12.2025 - 30.01.2026 | HMS 210
Einzeltermin | Do, 29.01.2026, 10:00 - Sa, 31.01.2026, 18:00 | extern | Exkursion zum Medienkunstfestival transmediale in Berlin
Inhalt: "As We May Think" is an essay written by Vannevar Bush in 1945, which has anticipated many technologies that we are using nowadays: personal computers, the internet, speech recognition, and online encyclopedias such as Wikipedia. But if Bush had focused his essay on language, could he have foreseen the digital tools we now use to process and generate language? Language, as something we consider what makes humans unique, has long posed exciting challenges for scientists and engineers since the dawn of information technology. How does a computer ‘understand’ and generate human language? What was the first chatbot and how was it built? Where lies the subtle line between the meaningful and the meaningless for both human and machine readers? This seminar explores these questions by combining theoretical discussions with practical coding exercises. Each week a practical technical topic will be introduced by the lecturer with code examples and exercises. Students will get the chance to generate computational poems, create their own chatbots, and delve into the creative and technical dimensions of Natural Language Processing (NLP). Python will serve as the primary programming languages for the course.
Tech Basics II - Lecture Stream A (Vorlesung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Dienstag | 09:45 - 11:30 | 13.10.2025 - 30.01.2026 | HMS 139
Inhalt: In this class, we’ll take the leap from software programming to physical computing. We will learn about the fundamentals of electronics, such as resistors, capacitors, potentiometers, and LEDs, and learn how to control them using a microcontroller— the Arduino. You’ll gain hands-on experience reading and interpreting schematics, prototyping circuits, and soldering components. While the focus is on hardware, there will still be some programming as well, but this time in C++.
Tech Basics II - Lecture Stream B (Vorlesung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Dienstag | 14:00 - 15:30 | 13.10.2025 - 30.01.2026 | HMS 139
Inhalt: In this class, we’ll take the leap from software programming to physical computing. We will learn about the fundamentals of electronics, such as resistors, capacitors, potentiometers, and LEDs, and learn how to control them using a microcontroller— the Arduino. You’ll gain hands-on experience reading and interpreting schematics, prototyping circuits, and soldering components. While the focus is on hardware, there will still be some programming as well, but this time in C++.
Tech Basics II - Exercise Stream A (Übung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Dienstag | 11:30 - 13:15 | 13.10.2025 - 30.01.2026 | HMS 139
Tech Basics II - Exercise Stream B (Übung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Dienstag | 15:30 - 17:30 | 13.10.2025 - 30.01.2026 | HMS 139
DATAx: Data analysis with Python (28) (Übung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Freitag | 16:00 - 16:55 | 13.10.2025 - 30.01.2026 | C 7.019 Seminarraum
Inhalt: This exercise introduces programming and data analysis using the Python programming language. It is specifically designed for students with no prior programming knowledge or experience. During the course, students will learn: - Basic programming concepts, such as variables, conditions, loops and functions. - Effective use of large language models (LLMs) in chat AI. - The essential steps for performing data analysis with Python. With the help of ready-made Jupyter notebooks, instructors from different disciplines supervise students' first practical experience of using Python in Jupyter notebooks, including sessions on data analysis and machine learning. Regular assignments encourage students to gain hands-on experience in programming and data analysis, and to apply their newfound knowledge to their field of study. By the end of the semester, students will work in a study group on a data-driven project, taking on different roles and learning to extract and present insights from real data together. Throughout the exercise, experienced and dedicated tutors (Teaching Assistants) are available to support students on campus. The languages of instruction in the tutorials are German and English.
DATAx: Data analysis with Python (29) (Übung)
Dozent/in: Qianxun Chen
Termin:
wöchentlich | Freitag | 17:00 - 17:55 | 13.10.2025 - 30.01.2026 | C 7.019 Seminarraum
Inhalt: This exercise introduces programming and data analysis using the Python programming language. It is specifically designed for students with no prior programming knowledge or experience. During the course, students will learn: - Basic programming concepts, such as variables, conditions, loops and functions. - Effective use of large language models (LLMs) in chat AI. - The essential steps for performing data analysis with Python. With the help of ready-made Jupyter notebooks, instructors from different disciplines supervise students' first practical experience of using Python in Jupyter notebooks, including sessions on data analysis and machine learning. Regular assignments encourage students to gain hands-on experience in programming and data analysis, and to apply their newfound knowledge to their field of study. By the end of the semester, students will work in a study group on a data-driven project, taking on different roles and learning to extract and present insights from real data together. Throughout the exercise, experienced and dedicated tutors (Teaching Assistants) are available to support students on campus. The languages of instruction in the tutorials are German and English.