070123 UE Methodological workshop - Artificial Intelligence and Large Language Models in Humanities Research (2023W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 11.09.2023 09:00 bis Mo 25.09.2023 14:00
- Anmeldung von Mi 27.09.2023 09:00 bis Fr 29.09.2023 14:00
- Abmeldung bis Di 31.10.2023 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Montag 02.10. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 09.10. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 16.10. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 23.10. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 30.10. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 06.11. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 13.11. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 20.11. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 27.11. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 04.12. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 11.12. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 08.01. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 15.01. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 22.01. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
- Montag 29.01. 09:00 - 10:30 Seminarraum Geschichte 3 Hauptgebäude, 2.Stock, Stiege 9
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
This course will introduce students to AI, its history and technological foundations, its ethical, legal, societal and economic issues, its applications, its current evolution and trajectory as well as the skills needed to use proven techniques to most effectively and efficiently interact with the leading tools on the market today as well as adapt to new ones.
Art der Leistungskontrolle und erlaubte Hilfsmittel
Students will be assessed based on four criteria:Classroom participation in discussions and prompt generation in class. (30%)
An individualized project which uses AI to solve a problem the proposal of which will be submitted to the Instructor by Week 9 and the final product of which will be submitted by Week 13. (25%)
The final project completed in a proctored room on Week 15 which will test the students’ prompt engineering skills in real time. (30%)
Each student must contribute to one of the three track-based projects which will be presented on Week 14. (15%)Please note, if a student misses more than one class, they will need to turn in a short written synopsis of the reading from that day.
An individualized project which uses AI to solve a problem the proposal of which will be submitted to the Instructor by Week 9 and the final product of which will be submitted by Week 13. (25%)
The final project completed in a proctored room on Week 15 which will test the students’ prompt engineering skills in real time. (30%)
Each student must contribute to one of the three track-based projects which will be presented on Week 14. (15%)Please note, if a student misses more than one class, they will need to turn in a short written synopsis of the reading from that day.
Mindestanforderungen und Beurteilungsmaßstab
Prüfungsstoff
Tracks
All students will be expected to attend all classes and practice the skill of prompt engineering across three types of AI interfaces based upon their input-output formats: Text to Text, Text to Image, and Text to Video.The students will, however, be able to choose a track based upon their personal interest starting in week 3. The track they choose will determine the group they are placed in for their “track-project” as well as the focus of their individual project.There are four specialized tracks based on the application of the skills students will develop:Economic Applications: Banking, Finance, Customer Service, E-Commerce, Sales and Marketing.
Cultural Applications: Fashion, Music, Design, Architecture, Video Game and Art Generation, Preservation and Restoration, Collaboration and Curation.
Educational Applications: Personalized learning, Student Support, Administrative Tasks, and Interactive Learning.
Policy Applications: Business, State and Regional Policy concerning AI development and use.
All students will be expected to attend all classes and practice the skill of prompt engineering across three types of AI interfaces based upon their input-output formats: Text to Text, Text to Image, and Text to Video.The students will, however, be able to choose a track based upon their personal interest starting in week 3. The track they choose will determine the group they are placed in for their “track-project” as well as the focus of their individual project.There are four specialized tracks based on the application of the skills students will develop:Economic Applications: Banking, Finance, Customer Service, E-Commerce, Sales and Marketing.
Cultural Applications: Fashion, Music, Design, Architecture, Video Game and Art Generation, Preservation and Restoration, Collaboration and Curation.
Educational Applications: Personalized learning, Student Support, Administrative Tasks, and Interactive Learning.
Policy Applications: Business, State and Regional Policy concerning AI development and use.
Literatur
Required Readings will be Excerpts provided to the students from the Following Texts:Russell, S., & Norvig, P. (2010). Artificial intelligence: A modern approach. Pearson.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Domingos, P. (2015). The master algorithm: How the quest for the ultimate learning machine will remake our world. Basic Books.
O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishers.
Murphy, K. P. (2012). Machine learning: A probabilistic perspective. MIT Press.
Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT Press.
Burkov, A. (2019). The hundred-page machine learning book. Andriy Burkov.
Géron, A. (2019). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O'Reilly Media.
Russell, S. (2019). Human compatible: Artificial intelligence and the problem of control. Viking.AI Tools:
Text to Text: Jasper AI, GrowthBar, ChatGPT, Frase, Copysmith.
Text to Image: Midjourney, Dream Studio- Stable Diffusion, Dall E 2, Photoshop Generative Fill.
Text to Video: Synthesia, Elai.io, Pictory, InVideo.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Domingos, P. (2015). The master algorithm: How the quest for the ultimate learning machine will remake our world. Basic Books.
O'Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishers.
Murphy, K. P. (2012). Machine learning: A probabilistic perspective. MIT Press.
Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT Press.
Burkov, A. (2019). The hundred-page machine learning book. Andriy Burkov.
Géron, A. (2019). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O'Reilly Media.
Russell, S. (2019). Human compatible: Artificial intelligence and the problem of control. Viking.AI Tools:
Text to Text: Jasper AI, GrowthBar, ChatGPT, Frase, Copysmith.
Text to Image: Midjourney, Dream Studio- Stable Diffusion, Dall E 2, Photoshop Generative Fill.
Text to Video: Synthesia, Elai.io, Pictory, InVideo.
Zuordnung im Vorlesungsverzeichnis
SP: Digital Humanities
Letzte Änderung: Mo 02.10.2023 00:04